fix: use vp for contracts generation in autofix workflow

Agent-Logs-Url: https://github.com/langgenius/dify/sessions/96ddc59c-309e-4f87-bb28-f326fbed9778

Co-authored-by: fatelei <961094+fatelei@users.noreply.github.com>

.github/scripts/reset-test-env.sh

@@ -1,709 +0,0 @@
-#!/usr/bin/env bash
-
-set -Eeuo pipefail
-
-SCRIPT_NAME="$(basename "$0")"
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd -P)"
-DEFAULT_REPO_ROOT="$(cd "$SCRIPT_DIR/../.." && pwd -P)"
-
-REPO_ROOT="${DIFY_REPO_ROOT:-$DEFAULT_REPO_ROOT}"
-YES=false
-DRY_RUN=true
-SKIP_SMOKE=false
-SKIP_MIGRATION=false
-TIMEOUT_SECONDS="${DIFY_RESET_TIMEOUT_SECONDS:-300}"
-SMOKE_URL="${DIFY_RESET_SMOKE_URL:-}"
-LOCK_DIR=""
-CURRENT_PHASE="init"
-
-DELETED_PATHS=()
-SKIPPED_PATHS=()
-DELETED_NAMED_VOLUMES=()
-SKIPPED_NAMED_VOLUMES=()
-PRESERVED_PATHS=()
-HEALTH_RESULTS=()
-SMOKE_RESULT="not-run"
-START_TIME="$(date +%s)"
-
-RUNTIME_PATHS=(
-  "volumes/db/data"
-  "volumes/mysql/data"
-  "volumes/redis/data"
-  "volumes/app/storage"
-  "volumes/plugin_daemon"
-  "volumes/weaviate"
-  "volumes/qdrant"
-  "volumes/pgvector"
-  "volumes/pgvecto_rs"
-  "volumes/chroma"
-  "volumes/milvus"
-  "volumes/opensearch/data"
-)
-
-NAMED_VOLUMES=(
-  "dify_es01_data"
-)
-
-PRESERVE_PATHS=(
-  ".env"
-  "middleware.env"
-  "docker-compose.yaml"
-  "docker-compose.middleware.yaml"
-  "nginx"
-  "ssrf_proxy"
-  "volumes/certbot"
-  "volumes/opensearch/opensearch_dashboards.yml"
-  "nginx/ssl"
-)
-
-usage() {
-  cat <<EOF
-Usage: $SCRIPT_NAME [options]
-
-Safely reset a Dify test environment in place. The command defaults to dry-run.
-
-Options:
-  --yes                  Perform destructive reset. Required to delete data.
-  --dry-run              Print planned actions without changing services or data.
-  --repo-root PATH       Repository root. Defaults to auto-detected Dify root.
-  --smoke-url URL        Public URL to verify after restart.
-  --skip-smoke           Skip public-domain smoke verification.
-  --skip-migration       Skip explicit migration gate.
-  --timeout SECONDS      Health-check timeout. Default: $TIMEOUT_SECONDS.
-  -h, --help             Show this help.
-
-Required for destructive reset:
-  ALLOW_DIFY_TEST_RESET=true
-  DIFY_ENV_NAME=test
-
-Optional:
-  DIFY_RESET_SMOKE_URL=https://test.example.com
-  RESET_TARGET_DOMAIN=test.example.com
-EOF
-}
-
-log() {
-  printf '[%s] %s\n' "$(date '+%Y-%m-%d %H:%M:%S')" "$*"
-}
-
-fail() {
-  local message="$1"
-  print_report "failure"
-  printf 'ERROR: %s\n' "$message" >&2
-  exit 1
-}
-
-run_cmd() {
-  printf '+'
-  printf ' %q' "$@"
-  printf '\n'
-  if [ "$DRY_RUN" = false ]; then
-    set +e
-    "$@"
-    local status=$?
-    set -e
-    if [ "$status" -ne 0 ]; then
-      fail "Command failed with exit code $status: $(command_string "$@")"
-    fi
-  fi
-}
-
-command_string() {
-  local arg
-  local result=""
-  for arg in "$@"; do
-    result="$result $(printf '%q' "$arg")"
-  done
-  printf '%s' "${result# }"
-}
-
-read_env_value() {
-  local key="$1"
-  local default_value="$2"
-  local env_file="$DOCKER_DIR/.env"
-  local value=""
-
-  if [ -f "$env_file" ]; then
-    value="$(awk -F= -v key="$key" '
-      $0 !~ /^[[:space:]]*#/ && $1 == key {
-        sub(/^[^=]*=/, "")
-        print
-      }
-    ' "$env_file" | tail -n 1)"
-  fi
-
-  if [ -z "$value" ]; then
-    printf '%s' "$default_value"
-    return
-  fi
-
-  value="${value%\"}"
-  value="${value#\"}"
-  value="${value%\'}"
-  value="${value#\'}"
-  printf '%s' "$value"
-}
-
-parse_args() {
-  while [ "$#" -gt 0 ]; do
-    case "$1" in
-      --yes)
-        YES=true
-        DRY_RUN=false
-        ;;
-      --dry-run)
-        DRY_RUN=true
-        ;;
-      --repo-root)
-        [ "$#" -ge 2 ] || fail "--repo-root requires a path"
-        REPO_ROOT="$2"
-        shift
-        ;;
-      --smoke-url)
-        [ "$#" -ge 2 ] || fail "--smoke-url requires a URL"
-        SMOKE_URL="$2"
-        shift
-        ;;
-      --skip-smoke)
-        SKIP_SMOKE=true
-        ;;
-      --skip-migration)
-        SKIP_MIGRATION=true
-        ;;
-      --timeout)
-        [ "$#" -ge 2 ] || fail "--timeout requires seconds"
-        TIMEOUT_SECONDS="$2"
-        shift
-        ;;
-      -h|--help)
-        usage
-        exit 0
-        ;;
-      *)
-        fail "Unknown option: $1"
-        ;;
-    esac
-    shift
-  done
-}
-
-validate_number() {
-  case "$TIMEOUT_SECONDS" in
-    ''|*[!0-9]*)
-      fail "--timeout must be a positive integer"
-      ;;
-  esac
-}
-
-require_docker() {
-  command -v docker >/dev/null 2>&1 || fail "docker command not found"
-  docker compose version >/dev/null 2>&1 || fail "docker compose is not available"
-}
-
-validate_environment() {
-  CURRENT_PHASE="validate"
-  REPO_ROOT="$(cd "$REPO_ROOT" && pwd -P)"
-  DOCKER_DIR="$REPO_ROOT/docker"
-
-  [ -d "$DOCKER_DIR" ] || fail "Docker directory not found: $DOCKER_DIR"
-  [ -f "$DOCKER_DIR/docker-compose.yaml" ] || fail "docker-compose.yaml not found in $DOCKER_DIR"
-  [ -f "$DOCKER_DIR/.env" ] || fail ".env not found in $DOCKER_DIR"
-
-  if [ "$DRY_RUN" = false ]; then
-    [ "$YES" = true ] || fail "Destructive reset requires --yes"
-    [ "${ALLOW_DIFY_TEST_RESET:-}" = "true" ] || fail "ALLOW_DIFY_TEST_RESET=true is required"
-    [ "${DIFY_ENV_NAME:-}" = "test" ] || fail "DIFY_ENV_NAME=test is required"
-    require_docker
-  fi
-}
-
-acquire_lock() {
-  CURRENT_PHASE="lock"
-  local env_name="${DIFY_ENV_NAME:-dry-run}"
-  LOCK_DIR="${TMPDIR:-/tmp}/dify-test-reset-${env_name}.lock"
-
-  if ! mkdir "$LOCK_DIR" 2>/dev/null; then
-    fail "Reset lock is already held: $LOCK_DIR"
-  fi
-
-  printf '%s\n' "$$" > "$LOCK_DIR/pid"
-  trap cleanup EXIT
-}
-
-cleanup() {
-  if [ -n "$LOCK_DIR" ] && [ -d "$LOCK_DIR" ]; then
-    rm -rf "$LOCK_DIR"
-  fi
-}
-
-compose() {
-  local args=(compose --env-file "$DOCKER_DIR/.env" -f "$DOCKER_DIR/docker-compose.yaml")
-  if [ -n "${DIFY_COMPOSE_PROJECT:-}" ]; then
-    args+=(-p "$DIFY_COMPOSE_PROJECT")
-  fi
-
-  docker "${args[@]}" "$@"
-}
-
-compose_project_name() {
-  if [ -n "${DIFY_COMPOSE_PROJECT:-}" ]; then
-    printf '%s' "$DIFY_COMPOSE_PROJECT"
-    return
-  fi
-
-  if [ -n "${COMPOSE_PROJECT_NAME:-}" ]; then
-    printf '%s' "$COMPOSE_PROJECT_NAME"
-    return
-  fi
-
-  local env_project
-  env_project="$(read_env_value COMPOSE_PROJECT_NAME "")"
-  if [ -n "$env_project" ]; then
-    printf '%s' "$env_project"
-    return
-  fi
-
-  basename "$DOCKER_DIR"
-}
-
-active_db_service() {
-  local db_type
-  db_type="$(read_env_value DB_TYPE postgresql)"
-  case "$db_type" in
-    postgresql|'')
-      printf '%s\n' "db_postgres"
-      ;;
-    mysql)
-      printf '%s\n' "db_mysql"
-      ;;
-    oceanbase)
-      printf '%s\n' "oceanbase"
-      ;;
-    *)
-      printf '%s\n' "$db_type"
-      ;;
-  esac
-}
-
-active_vector_service() {
-  local vector_store
-  vector_store="$(read_env_value VECTOR_STORE weaviate)"
-  case "$vector_store" in
-    ''|none|external)
-      return 0
-      ;;
-    pgvecto-rs|pgvecto_rs)
-      printf '%s\n' "pgvecto-rs"
-      ;;
-    milvus)
-      printf '%s\n' "milvus-standalone"
-      ;;
-    elasticsearch|opensearch|weaviate|qdrant|pgvector|chroma|oceanbase|seekdb|couchbase-server|iris)
-      printf '%s\n' "$vector_store"
-      ;;
-    couchbase)
-      printf '%s\n' "couchbase-server"
-      ;;
-    *)
-      return 0
-      ;;
-  esac
-}
-
-safe_runtime_path() {
-  local rel_path="$1"
-  case "$rel_path" in
-    ""|"/"| "." | ".." | *".."* | /*)
-      return 1
-      ;;
-  esac
-
-  case "$rel_path" in
-    volumes/*)
-      return 0
-      ;;
-    *)
-      return 1
-      ;;
-  esac
-}
-
-safe_named_volume() {
-  local volume="$1"
-  case "$volume" in
-    ""|*"/"*|*" "*|*$'\t'*|*$'\n'*|*$'\r'*)
-      return 1
-      ;;
-    *[!a-zA-Z0-9_.-]*)
-      return 1
-      ;;
-    *)
-      return 0
-      ;;
-  esac
-}
-
-volume_exists() {
-  docker volume inspect "$1" >/dev/null 2>&1
-}
-
-append_unique_volume() {
-  local candidate="$1"
-  local existing
-  [ -n "$candidate" ] || return 0
-
-  for existing in "${RESOLVED_VOLUME_NAMES[@]}"; do
-    if [ "$existing" = "$candidate" ]; then
-      return
-    fi
-  done
-
-  RESOLVED_VOLUME_NAMES+=("$candidate")
-}
-
-resolve_named_volume_names() {
-  local logical_name="$1"
-  local project_name
-  local candidate
-  local volume_list
-  local status
-  RESOLVED_VOLUME_NAMES=()
-
-  project_name="$(compose_project_name)"
-
-  set +e
-  volume_list="$(docker volume ls -q \
-    --filter "label=com.docker.compose.project=$project_name" \
-    --filter "label=com.docker.compose.volume=$logical_name" 2>/dev/null)"
-  status=$?
-  set -e
-
-  if [ "$status" -ne 0 ]; then
-    fail "Failed to list Docker volumes for Compose project $project_name"
-  fi
-
-  while IFS= read -r candidate; do
-    append_unique_volume "$candidate"
-  done <<< "$volume_list"
-
-  for candidate in "${project_name}_${logical_name}" "$logical_name"; do
-    if volume_exists "$candidate"; then
-      append_unique_volume "$candidate"
-    fi
-  done
-}
-
-collect_preserved_paths() {
-  PRESERVED_PATHS=()
-  local rel_path
-  for rel_path in "${PRESERVE_PATHS[@]}"; do
-    if [ -e "$DOCKER_DIR/$rel_path" ]; then
-      PRESERVED_PATHS+=("$rel_path")
-    fi
-  done
-}
-
-print_plan() {
-  CURRENT_PHASE="plan"
-  local db_service
-  local vector_service
-  db_service="$(active_db_service)"
-  vector_service="$(active_vector_service || true)"
-
-  collect_preserved_paths
-
-  log "Reset mode: $([ "$DRY_RUN" = true ] && printf dry-run || printf destructive)"
-  log "Repository root: $REPO_ROOT"
-  log "Docker directory: $DOCKER_DIR"
-  log "Compose project: $(compose_project_name)"
-  log "Database service: $db_service"
-  log "Vector service: ${vector_service:-<external-or-none>}"
-  log "Timeout: ${TIMEOUT_SECONDS}s"
-
-  printf '\nPlanned runtime path deletions:\n'
-  local rel_path
-  for rel_path in "${RUNTIME_PATHS[@]}"; do
-    printf '  - %s\n' "$rel_path"
-  done
-
-  printf '\nPlanned named volume deletions:\n'
-  local volume
-  for volume in "${NAMED_VOLUMES[@]}"; do
-    printf '  - %s (Compose project: %s)\n' "$volume" "$(compose_project_name)"
-  done
-
-  printf '\nPreserved configuration paths found:\n'
-  for rel_path in "${PRESERVED_PATHS[@]}"; do
-    printf '  - %s\n' "$rel_path"
-  done
-
-  printf '\nCommands:\n'
-  printf '  - docker compose down --remove-orphans\n'
-  printf '  - delete allowlisted runtime paths and named volumes\n'
-  printf '  - docker compose up -d %s redis%s\n' "$db_service" "${vector_service:+ $vector_service}"
-  printf '  - docker compose run --rm -e MIGRATION_ENABLED=true -e MODE=migration api\n'
-  printf '  - docker compose up -d\n'
-  printf '  - health checks and smoke check\n\n'
-}
-
-delete_runtime_paths() {
-  CURRENT_PHASE="delete-runtime-data"
-  local rel_path
-  local abs_path
-
-  for rel_path in "${RUNTIME_PATHS[@]}"; do
-    safe_runtime_path "$rel_path" || fail "Unsafe runtime path in allowlist: $rel_path"
-    abs_path="$DOCKER_DIR/$rel_path"
-
-    if [ ! -e "$abs_path" ]; then
-      SKIPPED_PATHS+=("$rel_path (absent)")
-      continue
-    fi
-
-    DELETED_PATHS+=("$rel_path")
-    run_cmd rm -rf -- "$abs_path"
-  done
-}
-
-delete_named_volumes() {
-  CURRENT_PHASE="delete-runtime-volumes"
-  local logical_name
-  local actual_name
-
-  for logical_name in "${NAMED_VOLUMES[@]}"; do
-    safe_named_volume "$logical_name" || fail "Unsafe named volume in allowlist: $logical_name"
-    resolve_named_volume_names "$logical_name"
-
-    if [ "${#RESOLVED_VOLUME_NAMES[@]}" -eq 0 ]; then
-      SKIPPED_NAMED_VOLUMES+=("$logical_name (absent)")
-      continue
-    fi
-
-    for actual_name in "${RESOLVED_VOLUME_NAMES[@]}"; do
-      DELETED_NAMED_VOLUMES+=("$actual_name")
-      run_cmd docker volume rm "$actual_name"
-    done
-  done
-}
-
-stop_stack() {
-  CURRENT_PHASE="stop-stack"
-  run_cmd compose down --remove-orphans
-}
-
-start_middleware() {
-  CURRENT_PHASE="start-middleware"
-  local db_service
-  local vector_service
-  local services=()
-
-  db_service="$(active_db_service)"
-  vector_service="$(active_vector_service || true)"
-  services+=("$db_service" "redis")
-
-  if [ -n "$vector_service" ]; then
-    services+=("$vector_service")
-  fi
-
-  run_cmd compose up -d "${services[@]}"
-  if [ "$DRY_RUN" = false ]; then
-    wait_for_services "${services[@]}"
-  fi
-}
-
-run_migration() {
-  CURRENT_PHASE="migration"
-  if [ "$SKIP_MIGRATION" = true ]; then
-    HEALTH_RESULTS+=("migration:skipped")
-    return
-  fi
-
-  run_cmd compose run --rm -e MIGRATION_ENABLED=true -e MODE=migration api
-  HEALTH_RESULTS+=("migration:ok")
-}
-
-start_full_stack() {
-  CURRENT_PHASE="start-full-stack"
-  run_cmd compose up -d
-
-  if [ "$DRY_RUN" = false ]; then
-    wait_for_services api web worker nginx
-    wait_if_service_exists plugin_daemon
-  fi
-}
-
-container_status() {
-  local service="$1"
-  local container_id
-  container_id="$(compose ps -q "$service" 2>/dev/null || true)"
-  [ -n "$container_id" ] || return 1
-
-  local health
-  health="$(docker inspect --format '{{if .State.Health}}{{.State.Health.Status}}{{else}}{{.State.Status}}{{end}}' "$container_id" 2>/dev/null || true)"
-  printf '%s' "$health"
-}
-
-wait_if_service_exists() {
-  local service="$1"
-  if [ -n "$(compose ps -q "$service" 2>/dev/null || true)" ]; then
-    wait_for_services "$service"
-  fi
-}
-
-wait_for_services() {
-  local service
-  for service in "$@"; do
-    wait_for_service "$service"
-  done
-}
-
-wait_for_service() {
-  local service="$1"
-  local deadline=$(( $(date +%s) + TIMEOUT_SECONDS ))
-  local status=""
-
-  log "Waiting for service: $service"
-  while [ "$(date +%s)" -le "$deadline" ]; do
-    status="$(container_status "$service" || true)"
-    case "$status" in
-      healthy|running)
-        HEALTH_RESULTS+=("$service:$status")
-        return 0
-        ;;
-      unhealthy|exited|dead)
-        HEALTH_RESULTS+=("$service:$status")
-        fail "Service $service reached failure status: $status"
-        ;;
-    esac
-    sleep 3
-  done
-
-  HEALTH_RESULTS+=("$service:timeout")
-  fail "Timed out waiting for service: $service"
-}
-
-default_smoke_url() {
-  if [ -n "$SMOKE_URL" ]; then
-    printf '%s' "$SMOKE_URL"
-    return
-  fi
-
-  if [ -n "${RESET_TARGET_DOMAIN:-}" ]; then
-    local https_enabled
-    https_enabled="$(read_env_value NGINX_HTTPS_ENABLED false)"
-    if [ "$https_enabled" = "true" ]; then
-      printf 'https://%s' "$RESET_TARGET_DOMAIN"
-    else
-      printf 'http://%s' "$RESET_TARGET_DOMAIN"
-    fi
-    return
-  fi
-
-  local port
-  port="$(read_env_value EXPOSE_NGINX_PORT 80)"
-  printf 'http://localhost:%s' "$port"
-}
-
-run_smoke_check() {
-  CURRENT_PHASE="smoke"
-  if [ "$SKIP_SMOKE" = true ]; then
-    SMOKE_RESULT="skipped"
-    return
-  fi
-
-  local url
-  url="$(default_smoke_url)"
-  if [ "$DRY_RUN" = true ]; then
-    SMOKE_RESULT="planned:$url"
-    printf '+ curl -fsS --max-time 10 %q\n' "$url"
-    return
-  fi
-
-  curl -fsS --max-time 10 "$url" >/dev/null || fail "Smoke check failed: $url"
-  SMOKE_RESULT="ok:$url"
-}
-
-print_report() {
-  local status="${1:-success}"
-  local end_time
-  end_time="$(date +%s)"
-
-  printf '\nReset report\n'
-  printf '============\n'
-  printf 'status: %s\n' "$status"
-  printf 'environment: %s\n' "${DIFY_ENV_NAME:-<unset>}"
-  printf 'repo_root: %s\n' "${REPO_ROOT:-<unset>}"
-  printf 'phase: %s\n' "$CURRENT_PHASE"
-  printf 'duration_seconds: %s\n' "$(( end_time - START_TIME ))"
-  printf 'mode: %s\n' "$([ "$DRY_RUN" = true ] && printf dry-run || printf destructive)"
-
-  printf '\ndeleted_runtime_paths:\n'
-  if [ "${#DELETED_PATHS[@]}" -eq 0 ]; then
-    printf '  - <none>\n'
-  else
-    printf '  - %s\n' "${DELETED_PATHS[@]}"
-  fi
-
-  printf '\nskipped_runtime_paths:\n'
-  if [ "${#SKIPPED_PATHS[@]}" -eq 0 ]; then
-    printf '  - <none>\n'
-  else
-    printf '  - %s\n' "${SKIPPED_PATHS[@]}"
-  fi
-
-  printf '\ndeleted_named_volumes:\n'
-  if [ "${#DELETED_NAMED_VOLUMES[@]}" -eq 0 ]; then
-    printf '  - <none>\n'
-  else
-    printf '  - %s\n' "${DELETED_NAMED_VOLUMES[@]}"
-  fi
-
-  printf '\nskipped_named_volumes:\n'
-  if [ "${#SKIPPED_NAMED_VOLUMES[@]}" -eq 0 ]; then
-    printf '  - <none>\n'
-  else
-    printf '  - %s\n' "${SKIPPED_NAMED_VOLUMES[@]}"
-  fi
-
-  printf '\npreserved_paths:\n'
-  if [ "${#PRESERVED_PATHS[@]}" -eq 0 ]; then
-    printf '  - <none found>\n'
-  else
-    printf '  - %s\n' "${PRESERVED_PATHS[@]}"
-  fi
-
-  printf '\nhealth_results:\n'
-  if [ "${#HEALTH_RESULTS[@]}" -eq 0 ]; then
-    printf '  - <not run>\n'
-  else
-    printf '  - %s\n' "${HEALTH_RESULTS[@]}"
-  fi
-
-  printf '\nsmoke_result: %s\n' "$SMOKE_RESULT"
-}
-
-main() {
-  parse_args "$@"
-  validate_number
-  validate_environment
-  acquire_lock
-  print_plan
-
-  if [ "$DRY_RUN" = true ]; then
-    run_smoke_check
-    print_report "dry-run"
-    return 0
-  fi
-
-  stop_stack
-  delete_runtime_paths
-  delete_named_volumes
-  start_middleware
-  run_migration
-  start_full_stack
-  run_smoke_check
-  CURRENT_PHASE="complete"
-  print_report "success"
-}
-
-main "$@"

.github/workflows/autofix.yml

@@ -120,7 +120,11 @@ jobs:
         if: github.event_name != 'merge_group' && steps.api-changes.outputs.any_changed == 'true'
         run: |
           cd api
-          uv run dev/generate_swagger_markdown_docs.py --swagger-dir openapi --markdown-dir openapi/markdown
+          uv run dev/generate_swagger_markdown_docs.py --swagger-dir ../packages/contracts/openapi --markdown-dir openapi/markdown --keep-swagger-json
+
+      - name: Generate frontend contracts
+        if: github.event_name != 'merge_group' && steps.api-changes.outputs.any_changed == 'true'
+        run: cd packages/contracts && vp run gen-api-contract-from-openapi
 
       - name: ESLint autofix
         if: github.event_name != 'merge_group' && steps.web-changes.outputs.any_changed == 'true'

.github/workflows/style.yml

@@ -77,6 +77,8 @@ jobs:
         with:
           files: |
             web/**
+            e2e/**
+            sdks/nodejs-client/**
             packages/**
             package.json
             pnpm-lock.yaml
@@ -94,14 +96,14 @@ jobs:
         id: eslint-cache-restore
         uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
         with:
-          path: web/.eslintcache
-          key: ${{ runner.os }}-web-eslint-${{ hashFiles('web/package.json', 'pnpm-lock.yaml', 'web/eslint.config.mjs', 'web/eslint.constants.mjs', 'web/plugins/eslint/**') }}-${{ github.sha }}
+          path: .eslintcache
+          key: ${{ runner.os }}-eslint-${{ hashFiles('pnpm-lock.yaml', 'eslint.config.mjs', 'web/eslint.config.mjs', 'web/eslint.constants.mjs', 'web/plugins/eslint/**') }}-${{ github.sha }}
           restore-keys: |
-            ${{ runner.os }}-web-eslint-${{ hashFiles('web/package.json', 'pnpm-lock.yaml', 'web/eslint.config.mjs', 'web/eslint.constants.mjs', 'web/plugins/eslint/**') }}-
+            ${{ runner.os }}-eslint-${{ hashFiles('pnpm-lock.yaml', 'eslint.config.mjs', 'web/eslint.config.mjs', 'web/eslint.constants.mjs', 'web/plugins/eslint/**') }}-
 
       - name: Web style check
         if: steps.changed-files.outputs.any_changed == 'true'
-        working-directory: ./web
+        working-directory: .
         run: vp run lint:ci
 
       - name: Web tsslint
@@ -113,7 +115,7 @@ jobs:
 
       - name: Web type check
         if: steps.changed-files.outputs.any_changed == 'true'
-        working-directory: ./web
+        working-directory: .
         run: vp run type-check
 
       - name: Web dead code check
@@ -125,7 +127,7 @@ jobs:
         if: steps.changed-files.outputs.any_changed == 'true' && success() && steps.eslint-cache-restore.outputs.cache-hit != 'true'
         uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
         with:
-          path: web/.eslintcache
+          path: .eslintcache
           key: ${{ steps.eslint-cache-restore.outputs.cache-primary-key }}
 
   superlinter:

.gitignore

@@ -203,6 +203,7 @@ sdks/python-client/dify_client.egg-info
 
 .vscode/*
 !.vscode/launch.json.template
+!.vscode/settings.example.json
 !.vscode/README.md
 api/.vscode
 # vscode Code History Extension
@@ -249,3 +250,5 @@ scripts/stress-test/reports/
 
 # Code Agent Folder
 .qoder/*
+.context/*
+.eslintcache

.vite-hooks/pre-commit

@@ -56,44 +56,9 @@ if $api_modified; then
     fi
 fi
 
-if $web_modified; then
-    if $skip_web_checks; then
-        echo "Git operation in progress, skipping web checks"
-        exit 0
-    fi
-
-    echo "Running ESLint on web module"
-
-    if git diff --cached --quiet -- 'web/**/*.ts' 'web/**/*.tsx'; then
-        web_ts_modified=false
-    else
-        ts_diff_status=$?
-        if [ $ts_diff_status -eq 1 ]; then
-            web_ts_modified=true
-        else
-            echo "Unable to determine staged TypeScript changes (git exit code: $ts_diff_status)."
-            exit $ts_diff_status
-        fi
-    fi
-
-    cd ./web || exit 1
-    pnpm exec vp staged
-
-    if $web_ts_modified; then
-        echo "Running TypeScript type-check:tsgo"
-        if ! npm run type-check:tsgo; then
-            echo "Type check failed. Please run 'npm run type-check:tsgo' to fix the errors."
-            exit 1
-        fi
-    else
-        echo "No staged TypeScript changes detected, skipping type-check:tsgo"
-    fi
-
-    echo "Running knip"
-    if ! npm run knip; then
-        echo "Knip check failed. Please run 'npm run knip' to fix the errors."
-        exit 1
-    fi
-
-    cd ../
+if $skip_web_checks; then
+    echo "Git operation in progress, skipping web checks"
+    exit 0
 fi
+
+vp staged

AGENTS.md

@@ -9,6 +9,7 @@ The codebase is split into:
 - **Backend API** (`/api`): Python Flask application organized with Domain-Driven Design
 - **Frontend Web** (`/web`): Next.js application using TypeScript and React
 - **Docker deployment** (`/docker`): Containerized deployment configurations
+- **Dify Agent Backend** (`/dify-agent`): Backend services for managing and executing agent
 
 ## Backend Workflow
 

Makefile

@@ -83,16 +83,15 @@ lint:
 	@echo "✅ Linting complete"
 
 type-check:
-	@echo "📝 Running type checks (basedpyright + pyrefly + mypy)..."
-	@./dev/basedpyright-check $(PATH_TO_CHECK)
-	@./dev/pyrefly-check-local
-	@uv --directory api run mypy --exclude-gitignore --exclude 'tests/' --exclude 'migrations/' --exclude 'dev/generate_swagger_specs.py' --check-untyped-defs --disable-error-code=import-untyped .
+	@echo "📝 Running type checks (pyrefly + mypy)..."
+	@./dev/pyrefly-check-local $(PATH_TO_CHECK)
+	@uv --directory api run mypy --exclude-gitignore --exclude 'tests/' --exclude 'migrations/' --exclude 'dev/generate_swagger_specs.py' --exclude 'dev/generate_fastopenapi_specs.py' --check-untyped-defs --disable-error-code=import-untyped .
 	@echo "✅ Type checks complete"
 
 type-check-core:
-	@echo "📝 Running core type checks (basedpyright + mypy)..."
-	@./dev/basedpyright-check $(PATH_TO_CHECK)
-	@uv --directory api run mypy --exclude-gitignore --exclude 'tests/' --exclude 'migrations/' --exclude 'dev/generate_swagger_specs.py'  --exclude 'dev/generate_fastopenapi_specs.py' --check-untyped-defs --disable-error-code=import-untyped .
+	@echo "📝 Running core type checks (pyrefly + mypy)..."
+	@./dev/pyrefly-check-local $(PATH_TO_CHECK)
+	@uv --directory api run mypy --exclude-gitignore --exclude 'tests/' --exclude 'migrations/' --exclude 'dev/generate_swagger_specs.py' --exclude 'dev/generate_fastopenapi_specs.py' --check-untyped-defs --disable-error-code=import-untyped .
 	@echo "✅ Core type checks complete"
 
 test:
@@ -153,8 +152,8 @@ help:
 	@echo "  make format         - Format code with ruff"
 	@echo "  make check          - Check code with ruff"
 	@echo "  make lint           - Format, fix, and lint code (ruff, imports, dotenv)"
-	@echo "  make type-check     - Run type checks (basedpyright, pyrefly, mypy)"
-	@echo "  make type-check-core - Run core type checks (basedpyright, mypy)"
+	@echo "  make type-check     - Run type checks (pyrefly, mypy)"
+	@echo "  make type-check-core - Run core type checks (pyrefly, mypy)"
 	@echo "  make test           - Run backend unit tests (or TARGET_TESTS=./api/tests/<target_tests>)"
 	@echo ""
 	@echo "Docker Build Targets:"

api/.env.example

@@ -557,7 +557,7 @@ MAX_VARIABLE_SIZE=204800
 
 # GraphEngine Worker Pool Configuration
 # Minimum number of workers per GraphEngine instance (default: 1)
-GRAPH_ENGINE_MIN_WORKERS=1
+GRAPH_ENGINE_MIN_WORKERS=3
 # Maximum number of workers per GraphEngine instance (default: 10)
 GRAPH_ENGINE_MAX_WORKERS=10
 # Queue depth threshold that triggers worker scale up (default: 3)

api/Dockerfile

@@ -17,14 +17,15 @@ FROM base AS packages
 RUN apt-get update \
     && apt-get install -y --no-install-recommends \
           # basic environment
-          git g++ \
+          g++ \
           # for building gmpy2
           libmpfr-dev libmpc-dev
 
 # Install Python dependencies (workspace members under providers/vdb/)
 COPY pyproject.toml uv.lock ./
 COPY providers ./providers
-RUN uv sync --locked --no-dev --group evaluation
+# Trust the checked-in lock during image builds; dev-only path sources live outside the api/ context.
+RUN uv sync --frozen --no-dev
 
 # production stage
 FROM base AS production
@@ -77,7 +78,6 @@ RUN \
     # Install dependencies
     && apt-get install -y --no-install-recommends \
         # basic environment
-        git \
         nodejs=${NODE_PACKAGE_VERSION} \
         # for gmpy2 \
         libgmp-dev libmpfr-dev libmpc-dev \

api/README.md

@@ -99,7 +99,7 @@ The scripts resolve paths relative to their location, so you can run them from a
    ./dev/reformat               # Run all formatters and linters
    uv run ruff check --fix ./   # Fix linting issues
    uv run ruff format ./        # Format code
-   uv run basedpyright .        # Type checking
+   uv run pyrefly check         # Type checking
    ```
 
 ## Generate TS stub

api/app_factory.py

@@ -117,7 +117,7 @@ def create_flask_app_with_configs() -> DifyApp:
             logger.warning("Failed to add trace headers to response", exc_info=True)
         return response
 
-    # Capture the decorator's return value to avoid pyright reportUnusedFunction
+    # Capture the decorator return values so static checkers do not treat the hooks as unused.
     _ = before_request
     _ = add_trace_headers
 

api/commands/__init__.py

@@ -4,7 +4,6 @@ CLI command modules extracted from `commands.py`.
 
 from .account import create_tenant, reset_email, reset_password
 from .plugin import (
-    backfill_plugin_auto_upgrade,
     extract_plugins,
     extract_unique_plugins,
     install_plugins,
@@ -15,7 +14,6 @@ from .plugin import (
     setup_system_trigger_oauth_client,
     transform_datasource_credentials,
 )
-from .rbac import migrate_member_roles_to_rbac
 from .retention import (
     archive_workflow_runs,
     clean_expired_messages,
@@ -39,7 +37,6 @@ from .vector import (
 __all__ = [
     "add_qdrant_index",
     "archive_workflow_runs",
-    "backfill_plugin_auto_upgrade",
     "clean_expired_messages",
     "clean_workflow_runs",
     "cleanup_orphaned_draft_variables",
@@ -58,7 +55,6 @@ __all__ = [
     "migrate_annotation_vector_database",
     "migrate_data_for_plugin",
     "migrate_knowledge_vector_database",
-    "migrate_member_roles_to_rbac",
     "migrate_oss",
     "old_metadata_migration",
     "remove_orphaned_files_on_storage",

api/commands/plugin.py

@@ -1,11 +1,10 @@
 import json
 import logging
-import time
 from typing import Any, cast
 
 import click
 from pydantic import TypeAdapter
-from sqlalchemy import delete, func, select
+from sqlalchemy import delete, select
 from sqlalchemy.engine import CursorResult
 
 from configs import dify_config
@@ -15,13 +14,11 @@ from core.plugin.impl.plugin import PluginInstaller
 from core.tools.utils.system_encryption import encrypt_system_params
 from extensions.ext_database import db
 from models import Tenant
-from models.account import TenantPluginAutoUpgradeStrategy
 from models.oauth import DatasourceOauthParamConfig, DatasourceProvider
 from models.provider_ids import DatasourceProviderID, ToolProviderID
 from models.source import DataSourceApiKeyAuthBinding, DataSourceOauthBinding
 from models.tools import ToolOAuthSystemClient
 from services.plugin.data_migration import PluginDataMigration
-from services.plugin.plugin_auto_upgrade_service import PluginAutoUpgradeService
 from services.plugin.plugin_migration import PluginMigration
 from services.plugin.plugin_service import PluginService
 
@@ -188,9 +185,9 @@ def transform_datasource_credentials(environment: str):
         firecrawl_plugin_id = "langgenius/firecrawl_datasource"
         jina_plugin_id = "langgenius/jina_datasource"
         if environment == "online":
-            notion_plugin_unique_identifier = plugin_migration._fetch_plugin_unique_identifier(notion_plugin_id)  # pyright: ignore[reportPrivateUsage]
-            firecrawl_plugin_unique_identifier = plugin_migration._fetch_plugin_unique_identifier(firecrawl_plugin_id)  # pyright: ignore[reportPrivateUsage]
-            jina_plugin_unique_identifier = plugin_migration._fetch_plugin_unique_identifier(jina_plugin_id)  # pyright: ignore[reportPrivateUsage]
+            notion_plugin_unique_identifier = plugin_migration._fetch_plugin_unique_identifier(notion_plugin_id)
+            firecrawl_plugin_unique_identifier = plugin_migration._fetch_plugin_unique_identifier(firecrawl_plugin_id)
+            jina_plugin_unique_identifier = plugin_migration._fetch_plugin_unique_identifier(jina_plugin_id)
         else:
             notion_plugin_unique_identifier = None
             firecrawl_plugin_unique_identifier = None
@@ -405,110 +402,6 @@ def migrate_data_for_plugin():
     click.echo(click.style("Migrate data for plugin completed.", fg="green"))
 
 
-def _candidate_auto_upgrade_strategy_tenant_ids_stmt(limit: int | None = None):
-    category_count = len(TenantPluginAutoUpgradeStrategy.PluginCategory)
-    stmt = (
-        select(TenantPluginAutoUpgradeStrategy.tenant_id)
-        .group_by(TenantPluginAutoUpgradeStrategy.tenant_id)
-        .having(func.count(func.distinct(TenantPluginAutoUpgradeStrategy.category)) < category_count)
-        .order_by(TenantPluginAutoUpgradeStrategy.tenant_id)
-    )
-
-    if limit is not None:
-        stmt = stmt.limit(limit)
-
-    return stmt
-
-
-def _count_auto_upgrade_strategy_tenant_ids(limit: int | None) -> int:
-    candidate_stmt = _candidate_auto_upgrade_strategy_tenant_ids_stmt(limit).subquery()
-    return db.session.scalar(select(func.count()).select_from(candidate_stmt)) or 0
-
-
-def _iter_auto_upgrade_strategy_tenant_ids(limit: int | None):
-    stmt = _candidate_auto_upgrade_strategy_tenant_ids_stmt(limit).execution_options(yield_per=1000)
-    yield from db.session.scalars(stmt)
-
-
-@click.command(
-    "backfill-plugin-auto-upgrade",
-    help="Backfill category-scoped plugin auto-upgrade strategies and normalize plugin lists.",
-)
-@click.option("--tenant-id", multiple=True, help="Tenant ID to backfill. Can be passed multiple times.")
-@click.option("--limit", type=int, default=None, help="Maximum number of candidate tenants to process.")
-@click.option("--batch-size", type=int, default=500, show_default=True, help="Progress reporting batch size.")
-@click.option("--dry-run", is_flag=True, help="Only print candidate tenant count.")
-def backfill_plugin_auto_upgrade(
-    tenant_id: tuple[str, ...],
-    limit: int | None,
-    batch_size: int,
-    dry_run: bool,
-):
-    """
-    Backfill historical auto-upgrade strategies after the category column exists.
-
-    Missing category rows are created from the tenant's tool/default row. Pure default
-    strategies become latest for model plugins and fix-only for all other categories.
-    Tenants with include/exclude plugin IDs are split
-    by installed plugin category using plugin daemon metadata.
-    """
-    start_at = time.perf_counter()
-    candidate_count = len(tenant_id) if tenant_id else _count_auto_upgrade_strategy_tenant_ids(limit)
-    click.echo(click.style(f"Found {candidate_count} candidate tenants.", fg="yellow"))
-
-    if dry_run:
-        elapsed = time.perf_counter() - start_at
-        click.echo(click.style(f"Dry run completed. elapsed={elapsed:.2f}s", fg="green"))
-        return
-
-    tenant_ids = list(tenant_id) if tenant_id else _iter_auto_upgrade_strategy_tenant_ids(limit)
-
-    backfilled_count = 0
-    created_count = 0
-    normalized_count = 0
-    skipped_count = 0
-    failed_count = 0
-    for index, current_tenant_id in enumerate(tenant_ids, start=1):
-        try:
-            result = PluginAutoUpgradeService.backfill_strategy_categories(
-                current_tenant_id,
-            )
-        except Exception as e:
-            failed_count += 1
-            click.echo(click.style(f"Failed tenant {current_tenant_id}: {str(e)}", fg="red"))
-            continue
-
-        if result.created_count > 0:
-            backfilled_count += 1
-            created_count += result.created_count
-        elif not result.normalized:
-            skipped_count += 1
-        if result.normalized:
-            normalized_count += 1
-
-        if batch_size > 0 and index % batch_size == 0:
-            click.echo(
-                click.style(
-                    f"Processed {index}/{candidate_count} tenants. "
-                    f"backfilled={backfilled_count}, created_rows={created_count}, "
-                    f"normalized={normalized_count}, skipped={skipped_count}, failed={failed_count}, "
-                    f"elapsed={time.perf_counter() - start_at:.2f}s",
-                    fg="yellow",
-                )
-            )
-
-    elapsed = time.perf_counter() - start_at
-    click.echo(
-        click.style(
-            f"Backfill plugin auto-upgrade strategy categories completed. "
-            f"backfilled={backfilled_count}, created_rows={created_count}, "
-            f"normalized={normalized_count}, skipped={skipped_count}, failed={failed_count}, "
-            f"elapsed={elapsed:.2f}s",
-            fg="green",
-        )
-    )
-
-
 @click.command("extract-plugins", help="Extract plugins.")
 @click.option("--output_file", prompt=True, help="The file to store the extracted plugins.", default="plugins.jsonl")
 @click.option("--workers", prompt=True, help="The number of workers to extract plugins.", default=10)

api/commands/rbac.py

@@ -1,109 +0,0 @@
-from __future__ import annotations
-
-import click
-from sqlalchemy import select
-
-from core.db.session_factory import session_factory
-from models import TenantAccountJoin, TenantAccountRole
-from services.enterprise.rbac_service import ListOption, RBACService
-
-
-def _resolve_builtin_role_id(tenant_id: str, operator_account_id: str, legacy_role: str) -> str:
-    """Resolve a legacy workspace role to the current tenant's builtin RBAC role id.
-
-    The migration replays the old `TenantAccountJoin.role` values onto the
-    RBAC member-role binding API. Builtin RBAC roles are tenant-scoped and
-    identified by runtime ids, so the command must look them up per tenant.
-    """
-    expected_builtin_name = {
-        TenantAccountRole.OWNER.value: "所有者",
-        TenantAccountRole.ADMIN.value: "管理者",
-        TenantAccountRole.EDITOR.value: "编辑者",
-        TenantAccountRole.NORMAL.value: "普通用户",
-        TenantAccountRole.DATASET_OPERATOR.value: "知识库操作员",
-    }.get(legacy_role)
-    if not expected_builtin_name:
-        raise ValueError(f"Unsupported legacy workspace role: {legacy_role}")
-
-    roles = RBACService.Roles.list(
-        tenant_id=tenant_id,
-        account_id=operator_account_id,
-        options=ListOption(page_number=1, results_per_page=100),
-    ).data
-    for role in roles:
-        if role.is_builtin and role.category == "global_system_default" and role.name == expected_builtin_name:
-            return str(role.id)
-
-    raise ValueError(f"Builtin RBAC role not found for tenant={tenant_id}, legacy_role={legacy_role}")
-
-
-@click.command("rbac-migrate-member-roles", help="Migrate legacy workspace member roles into RBAC member-role bindings.")
-@click.option("--tenant-id", help="Only migrate a single workspace.")
-@click.option("--dry-run", is_flag=True, default=False, help="Preview the migration without writing RBAC bindings.")
-def migrate_member_roles_to_rbac(tenant_id: str | None, dry_run: bool) -> None:
-    """Backfill RBAC member-role bindings from legacy `TenantAccountJoin.role` data.
-
-    This is an offline migration command for workspaces that already have
-    members in the legacy role model but need matching records in the RBAC
-    member-role binding store.
-    """
-    click.echo(click.style("Starting RBAC member-role migration.", fg="green"))
-
-    with session_factory.create_session() as session:
-        stmt = select(TenantAccountJoin).order_by(TenantAccountJoin.tenant_id.asc(), TenantAccountJoin.id.asc())
-        if tenant_id:
-            stmt = stmt.where(TenantAccountJoin.tenant_id == tenant_id)
-
-        joins = list(session.scalars(stmt).all())
-
-    if not joins:
-        click.echo(click.style("No workspace members found for migration.", fg="yellow"))
-        return
-
-    owner_account_by_tenant: dict[str, str] = {}
-    resolved_role_ids: dict[tuple[str, str], str] = {}
-    migrated_count = 0
-
-    for join in joins:
-        workspace_id = str(join.tenant_id)
-        member_account_id = str(join.account_id)
-        legacy_role = str(join.role)
-
-        if workspace_id not in owner_account_by_tenant:
-            owner_join = next(
-                (
-                    item
-                    for item in joins
-                    if str(item.tenant_id) == workspace_id and str(item.role) == TenantAccountRole.OWNER.value
-                ),
-                None,
-            )
-            if not owner_join:
-                raise ValueError(f"Workspace owner not found for tenant={workspace_id}")
-            owner_account_by_tenant[workspace_id] = str(owner_join.account_id)
-
-        operator_account_id = owner_account_by_tenant[workspace_id]
-        cache_key = (workspace_id, legacy_role)
-        if cache_key not in resolved_role_ids:
-            resolved_role_ids[cache_key] = _resolve_builtin_role_id(workspace_id, operator_account_id, legacy_role)
-
-        resolved_role_id = resolved_role_ids[cache_key]
-        click.echo(
-            f"tenant={workspace_id} member={member_account_id} legacy_role={legacy_role} -> rbac_role_id={resolved_role_id}"
-        )
-
-        if dry_run:
-            continue
-
-        RBACService.MemberRoles.replace(
-            tenant_id=workspace_id,
-            account_id=operator_account_id,
-            member_account_id=member_account_id,
-            role_ids=[resolved_role_id],
-        )
-        migrated_count += 1
-
-    if dry_run:
-        click.echo(click.style("Dry run completed. No RBAC bindings were written.", fg="yellow"))
-    else:
-        click.echo(click.style(f"RBAC member-role migration completed. Migrated {migrated_count} members.", fg="green"))

api/commands/system.py

@@ -14,6 +14,7 @@ from libs.rsa import generate_key_pair
 from models import Tenant
 from models.model import App, AppMode, Conversation
 from models.provider import Provider, ProviderModel
+from models.tools import ApiToolProvider, BuiltinToolProvider, MCPToolProvider
 
 logger = logging.getLogger(__name__)
 
@@ -23,13 +24,16 @@ DB_UPGRADE_LOCK_TTL_SECONDS = 60
 @click.command(
     "reset-encrypt-key-pair",
     help="Reset the asymmetric key pair of workspace for encrypt LLM credentials. "
-    "After the reset, all LLM credentials will become invalid, "
-    "requiring re-entry."
+    "After the reset, all LLM credentials and tool provider credentials "
+    "(builtin / API / MCP) will be purged, requiring re-entry. "
     "Only support SELF_HOSTED mode.",
 )
 @click.confirmation_option(
     prompt=click.style(
-        "Are you sure you want to reset encrypt key pair? This operation cannot be rolled back!", fg="red"
+        "Are you sure you want to reset encrypt key pair? "
+        "This will also purge builtin / API / MCP tool provider records for every tenant. "
+        "This operation cannot be rolled back!",
+        fg="red",
     )
 )
 def reset_encrypt_key_pair():
@@ -53,6 +57,13 @@ def reset_encrypt_key_pair():
             session.execute(delete(Provider).where(Provider.provider_type == "custom", Provider.tenant_id == tenant.id))
             session.execute(delete(ProviderModel).where(ProviderModel.tenant_id == tenant.id))
 
+            # Purge tool provider records that hold credentials encrypted under the
+            # tenant key. Leaving them in place causes /console/api/workspaces/current/
+            # tool-providers to 500 because decryption fails on stale ciphertext (#35396).
+            session.execute(delete(BuiltinToolProvider).where(BuiltinToolProvider.tenant_id == tenant.id))
+            session.execute(delete(ApiToolProvider).where(ApiToolProvider.tenant_id == tenant.id))
+            session.execute(delete(MCPToolProvider).where(MCPToolProvider.tenant_id == tenant.id))
+
             click.echo(
                 click.style(
                     f"Congratulations! The asymmetric key pair of workspace {tenant.id} has been reset.",

api/configs/enterprise/__init__.py

@@ -23,9 +23,10 @@ class EnterpriseFeatureConfig(BaseSettings):
         ge=1, description="Maximum timeout in seconds for enterprise requests", default=5
     )
 
-    RBAC_ENABLED: bool = Field(
-        description="Enable enterprise RBAC APIs. When disabled, compatibility responses fall back to legacy roles.",
+    ENTERPRISE_DISABLE_RUNTIME_CREDENTIAL_CHECK: bool = Field(
         default=False,
+        description="If disabled, credential policy check is only performed when saving workflows."
+        "This helps gain runtime performance by trading off consistency.",
     )
 
 

api/configs/feature/__init__.py

@@ -761,7 +761,7 @@ class WorkflowConfig(BaseSettings):
     # GraphEngine Worker Pool Configuration
     GRAPH_ENGINE_MIN_WORKERS: PositiveInt = Field(
         description="Minimum number of workers per GraphEngine instance",
-        default=1,
+        default=3,
     )
 
     GRAPH_ENGINE_MAX_WORKERS: PositiveInt = Field(
@@ -1406,32 +1406,6 @@ class SandboxExpiredRecordsCleanConfig(BaseSettings):
     )
 
 
-class EvaluationConfig(BaseSettings):
-    """
-    Configuration for evaluation runtime
-    """
-
-    EVALUATION_FRAMEWORK: str = Field(
-        description="Evaluation framework to use (ragas/deepeval/none)",
-        default="none",
-    )
-
-    EVALUATION_MAX_CONCURRENT_RUNS: PositiveInt = Field(
-        description="Maximum number of concurrent evaluation runs per tenant",
-        default=3,
-    )
-
-    EVALUATION_MAX_DATASET_ROWS: PositiveInt = Field(
-        description="Maximum number of rows allowed in an evaluation dataset",
-        default=500,
-    )
-
-    EVALUATION_TASK_TIMEOUT: PositiveInt = Field(
-        description="Timeout in seconds for a single evaluation task",
-        default=3600,
-    )
-
-
 class FeatureConfig(
     # place the configs in alphabet order
     AppExecutionConfig,
@@ -1445,7 +1419,6 @@ class FeatureConfig(
     MarketplaceConfig,
     DataSetConfig,
     EndpointConfig,
-    EvaluationConfig,
     FileAccessConfig,
     FileUploadConfig,
     HttpConfig,

api/configs/middleware/__init__.py

@@ -1,5 +1,5 @@
 import os
-from typing import Any, Literal, TypedDict
+from typing import Any, Literal, TypedDict, cast
 from urllib.parse import parse_qsl, quote_plus
 
 from pydantic import Field, NonNegativeFloat, NonNegativeInt, PositiveFloat, PositiveInt, computed_field
@@ -50,28 +50,30 @@ from .vdb.vastbase_vector_config import VastbaseVectorConfig
 from .vdb.vikingdb_config import VikingDBConfig
 from .vdb.weaviate_config import WeaviateConfig
 
+_VALID_STORAGE_TYPE = Literal[
+    "opendal",
+    "s3",
+    "aliyun-oss",
+    "azure-blob",
+    "baidu-obs",
+    "clickzetta-volume",
+    "google-storage",
+    "huawei-obs",
+    "oci-storage",
+    "tencent-cos",
+    "volcengine-tos",
+    "supabase",
+    "local",
+]
+
 
 class StorageConfig(BaseSettings):
-    STORAGE_TYPE: Literal[
-        "opendal",
-        "s3",
-        "aliyun-oss",
-        "azure-blob",
-        "baidu-obs",
-        "clickzetta-volume",
-        "google-storage",
-        "huawei-obs",
-        "oci-storage",
-        "tencent-cos",
-        "volcengine-tos",
-        "supabase",
-        "local",
-    ] = Field(
+    STORAGE_TYPE: _VALID_STORAGE_TYPE = Field(
         description="Type of storage to use."
         " Options: 'opendal', '(deprecated) local', 's3', 'aliyun-oss', 'azure-blob', 'baidu-obs', "
         "'clickzetta-volume', 'google-storage', 'huawei-obs', 'oci-storage', 'tencent-cos', "
         "'volcengine-tos', 'supabase'. Default is 'opendal'.",
-        default="opendal",
+        default=cast(_VALID_STORAGE_TYPE, "opendal"),
     )
 
     STORAGE_LOCAL_PATH: str = Field(

api/controllers/common/human_input.py

@@ -1,36 +1,21 @@
-from pydantic import BaseModel, Field, JsonValue
+import json
 
-HUMAN_INPUT_FORM_INPUT_EXAMPLE = {
-    "decision": "approve",
-    "attachment": {
-        "transfer_method": "local_file",
-        "upload_file_id": "4e0d1b87-52f2-49f6-b8c6-95cd9c954b3e",
-        "type": "document",
-    },
-    "attachments": [
-        {
-            "transfer_method": "local_file",
-            "upload_file_id": "1a77f0df-c0e6-461c-987c-e72526f341ee",
-            "type": "document",
-        },
-        {
-            "transfer_method": "remote_url",
-            "url": "https://example.com/report.pdf",
-            "type": "document",
-        },
-    ],
-}
+from pydantic import BaseModel, JsonValue
 
 
 class HumanInputFormSubmitPayload(BaseModel):
-    inputs: dict[str, JsonValue] = Field(
-        description=(
-            "Submitted human input values keyed by output variable name. "
-            "Use a string for paragraph or select input values, a file mapping for file inputs, "
-            "and a list of file mappings for file-list inputs. Local file mappings use "
-            "`transfer_method=local_file` with `upload_file_id`; remote file mappings use "
-            "`transfer_method=remote_url` with `url` or `remote_url`."
-        ),
-        examples=[HUMAN_INPUT_FORM_INPUT_EXAMPLE],
-    )
+    inputs: dict[str, JsonValue]
     action: str
+
+
+def stringify_form_default_values(values: dict[str, object]) -> dict[str, str]:
+    """Serialize default values into strings expected by human-input form clients."""
+    result: dict[str, str] = {}
+    for key, value in values.items():
+        if value is None:
+            result[key] = ""
+        elif isinstance(value, (dict, list)):
+            result[key] = json.dumps(value, ensure_ascii=False)
+        else:
+            result[key] = str(value)
+    return result

api/controllers/common/schema.py

@@ -39,6 +39,7 @@ QueryParamDoc = TypedDict(
 def _register_json_schema(namespace: Namespace, name: str, schema: dict) -> None:
     """Register a JSON schema and promote any nested Pydantic `$defs`."""
 
+    schema = _swagger_2_compatible_schema(schema)
     nested_definitions = schema.get("$defs")
     schema_to_register = dict(schema)
     if isinstance(nested_definitions, dict):
@@ -65,6 +66,35 @@ def _register_schema_model(namespace: Namespace, model: type[BaseModel], *, mode
     )
 
 
+def _swagger_2_compatible_schema(value: Any) -> Any:
+    if isinstance(value, list):
+        return [_swagger_2_compatible_schema(item) for item in value]
+
+    if not isinstance(value, dict):
+        return value
+
+    converted = {key: _swagger_2_compatible_schema(child) for key, child in value.items()}
+    any_of = value.get("anyOf")
+    if not isinstance(any_of, list):
+        return converted
+
+    non_null_candidates = [
+        candidate for candidate in any_of if isinstance(candidate, Mapping) and candidate.get("type") != "null"
+    ]
+    has_null_candidate = any(isinstance(candidate, Mapping) and candidate.get("type") == "null" for candidate in any_of)
+    if not has_null_candidate or len(non_null_candidates) != 1:
+        return converted
+
+    non_null_schema = _swagger_2_compatible_schema(dict(non_null_candidates[0]))
+    if not isinstance(non_null_schema, dict):
+        return converted
+
+    converted.pop("anyOf", None)
+    converted.update(non_null_schema)
+    converted["x-nullable"] = True
+    return converted
+
+
 def register_schema_model(namespace: Namespace, model: type[BaseModel]) -> None:
     """Register a BaseModel and its nested schema definitions for Swagger documentation."""
 

api/controllers/console/__init__.py

@@ -33,7 +33,6 @@ for module_name in RESOURCE_MODULES:
 # Ensure resource modules are imported so route decorators are evaluated.
 # Import other controllers
 from . import (
-    admin,
     apikey,
     extension,
     feature,
@@ -108,9 +107,6 @@ from .datasets.rag_pipeline import (
     rag_pipeline_workflow,
 )
 
-# Import evaluation controllers
-from .evaluation import evaluation
-
 # Import explore controllers
 from .explore import (
     banner,
@@ -120,12 +116,8 @@ from .explore import (
     saved_message,
     trial,
 )
+from .socketio import workflow as socketio_workflow
 
-# Import snippet controllers
-from .snippets import snippet_workflow, snippet_workflow_draft_variable
-from .socketio import workflow as socketio_workflow  # pyright: ignore[reportUnusedImport]
-
-# Import snippet controllers
 # Import tag controllers
 from .tag import tags
 
@@ -139,8 +131,6 @@ from .workspace import (
     model_providers,
     models,
     plugin,
-    rbac,
-    snippets,
     tool_providers,
     trigger_providers,
     workspace,
@@ -151,7 +141,6 @@ api.add_namespace(console_ns)
 __all__ = [
     "account",
     "activate",
-    "admin",
     "advanced_prompt_template",
     "agent",
     "agent_providers",
@@ -178,7 +167,6 @@ __all__ = [
     "datasource_content_preview",
     "email_register",
     "endpoint",
-    "evaluation",
     "extension",
     "external",
     "feature",
@@ -209,17 +197,10 @@ __all__ = [
     "rag_pipeline_draft_variable",
     "rag_pipeline_import",
     "rag_pipeline_workflow",
-    "rbac",
     "recommended_app",
     "saved_message",
     "setup",
     "site",
-    "snippet_workflow",
-    "snippet_workflow",
-    "snippet_workflow_draft_variable",
-    "snippet_workflow_draft_variable",
-    "snippets",
-    "snippets",
     "socketio_workflow",
     "spec",
     "statistic",

api/controllers/console/admin.py

@@ -1,64 +1,11 @@
-import csv
-import io
 from collections.abc import Callable
 from functools import wraps
-from typing import cast
-from uuid import UUID
 
 from flask import request
-from flask_restx import Resource
-from pydantic import BaseModel, Field, field_validator
-from sqlalchemy import select
-from werkzeug.exceptions import BadRequest, NotFound, Unauthorized
+from werkzeug.exceptions import Unauthorized
 
 from configs import dify_config
-from constants.languages import supported_language
-from controllers.common.schema import register_schema_models
-from controllers.console import console_ns
-from controllers.console.wraps import only_edition_cloud
-from core.db.session_factory import session_factory
-from extensions.ext_database import db
 from libs.token import extract_access_token
-from models.model import App, ExporleBanner, InstalledApp, RecommendedApp, TrialApp
-from services.billing_service import BillingService, LangContentDict
-
-
-class InsertExploreAppPayload(BaseModel):
-    app_id: str = Field(...)
-    desc: str | None = None
-    copyright: str | None = None
-    privacy_policy: str | None = None
-    custom_disclaimer: str | None = None
-    language: str = Field(...)
-    category: str = Field(...)
-    position: int = Field(...)
-    can_trial: bool = Field(default=False)
-    trial_limit: int = Field(default=0)
-
-    @field_validator("language")
-    @classmethod
-    def validate_language(cls, value: str) -> str:
-        return supported_language(value)
-
-
-class InsertExploreBannerPayload(BaseModel):
-    category: str = Field(...)
-    title: str = Field(...)
-    description: str = Field(...)
-    img_src: str = Field(..., alias="img-src")
-    language: str = Field(default="en-US")
-    link: str = Field(...)
-    sort: int = Field(...)
-
-    @field_validator("language")
-    @classmethod
-    def validate_language(cls, value: str) -> str:
-        return supported_language(value)
-
-    model_config = {"populate_by_name": True}
-
-
-register_schema_models(console_ns, InsertExploreAppPayload, InsertExploreBannerPayload)
 
 
 def admin_required[**P, R](view: Callable[P, R]) -> Callable[P, R]:
@@ -76,353 +23,3 @@ def admin_required[**P, R](view: Callable[P, R]) -> Callable[P, R]:
         return view(*args, **kwargs)
 
     return decorated
-
-
-@console_ns.route("/admin/insert-explore-apps")
-class InsertExploreAppListApi(Resource):
-    @console_ns.doc("insert_explore_app")
-    @console_ns.doc(description="Insert or update an app in the explore list")
-    @console_ns.expect(console_ns.models[InsertExploreAppPayload.__name__])
-    @console_ns.response(200, "App updated successfully")
-    @console_ns.response(201, "App inserted successfully")
-    @console_ns.response(404, "App not found")
-    @only_edition_cloud
-    @admin_required
-    def post(self):
-        payload = InsertExploreAppPayload.model_validate(console_ns.payload)
-
-        app = db.session.execute(select(App).where(App.id == payload.app_id)).scalar_one_or_none()
-        if not app:
-            raise NotFound(f"App '{payload.app_id}' is not found")
-
-        site = app.site
-        if not site:
-            desc = payload.desc or ""
-            copy_right = payload.copyright or ""
-            privacy_policy = payload.privacy_policy or ""
-            custom_disclaimer = payload.custom_disclaimer or ""
-        else:
-            desc = site.description or payload.desc or ""
-            copy_right = site.copyright or payload.copyright or ""
-            privacy_policy = site.privacy_policy or payload.privacy_policy or ""
-            custom_disclaimer = site.custom_disclaimer or payload.custom_disclaimer or ""
-
-        with session_factory.create_session() as session:
-            recommended_app = session.execute(
-                select(RecommendedApp).where(RecommendedApp.app_id == payload.app_id)
-            ).scalar_one_or_none()
-
-            if not recommended_app:
-                recommended_app = RecommendedApp(
-                    app_id=app.id,
-                    description=desc,
-                    copyright=copy_right,
-                    privacy_policy=privacy_policy,
-                    custom_disclaimer=custom_disclaimer,
-                    language=payload.language,
-                    category=payload.category,
-                    position=payload.position,
-                )
-
-                db.session.add(recommended_app)
-                if payload.can_trial:
-                    trial_app = db.session.execute(
-                        select(TrialApp).where(TrialApp.app_id == payload.app_id)
-                    ).scalar_one_or_none()
-                    if not trial_app:
-                        db.session.add(
-                            TrialApp(
-                                app_id=payload.app_id,
-                                tenant_id=app.tenant_id,
-                                trial_limit=payload.trial_limit,
-                            )
-                        )
-                    else:
-                        trial_app.trial_limit = payload.trial_limit
-
-                app.is_public = True
-                db.session.commit()
-
-                return {"result": "success"}, 201
-            else:
-                recommended_app.description = desc
-                recommended_app.copyright = copy_right
-                recommended_app.privacy_policy = privacy_policy
-                recommended_app.custom_disclaimer = custom_disclaimer
-                recommended_app.language = payload.language
-                recommended_app.category = payload.category
-                recommended_app.position = payload.position
-
-                if payload.can_trial:
-                    trial_app = db.session.execute(
-                        select(TrialApp).where(TrialApp.app_id == payload.app_id)
-                    ).scalar_one_or_none()
-                    if not trial_app:
-                        db.session.add(
-                            TrialApp(
-                                app_id=payload.app_id,
-                                tenant_id=app.tenant_id,
-                                trial_limit=payload.trial_limit,
-                            )
-                        )
-                    else:
-                        trial_app.trial_limit = payload.trial_limit
-                app.is_public = True
-
-                db.session.commit()
-
-                return {"result": "success"}, 200
-
-
-@console_ns.route("/admin/insert-explore-apps/<uuid:app_id>")
-class InsertExploreAppApi(Resource):
-    @console_ns.doc("delete_explore_app")
-    @console_ns.doc(description="Remove an app from the explore list")
-    @console_ns.doc(params={"app_id": "Application ID to remove"})
-    @console_ns.response(204, "App removed successfully")
-    @only_edition_cloud
-    @admin_required
-    def delete(self, app_id: UUID):
-        with session_factory.create_session() as session:
-            recommended_app = session.execute(
-                select(RecommendedApp).where(RecommendedApp.app_id == str(app_id))
-            ).scalar_one_or_none()
-
-        if not recommended_app:
-            return {"result": "success"}, 204
-
-        with session_factory.create_session() as session:
-            app = session.execute(select(App).where(App.id == recommended_app.app_id)).scalar_one_or_none()
-
-        if app:
-            app.is_public = False
-
-        with session_factory.create_session() as session:
-            installed_apps = (
-                session.execute(
-                    select(InstalledApp).where(
-                        InstalledApp.app_id == recommended_app.app_id,
-                        InstalledApp.tenant_id != InstalledApp.app_owner_tenant_id,
-                    )
-                )
-                .scalars()
-                .all()
-            )
-
-            for installed_app in installed_apps:
-                session.delete(installed_app)
-
-            trial_app = session.execute(
-                select(TrialApp).where(TrialApp.app_id == recommended_app.app_id)
-            ).scalar_one_or_none()
-            if trial_app:
-                session.delete(trial_app)
-
-        db.session.delete(recommended_app)
-        db.session.commit()
-
-        return {"result": "success"}, 204
-
-
-@console_ns.route("/admin/insert-explore-banner")
-class InsertExploreBannerApi(Resource):
-    @console_ns.doc("insert_explore_banner")
-    @console_ns.doc(description="Insert an explore banner")
-    @console_ns.expect(console_ns.models[InsertExploreBannerPayload.__name__])
-    @console_ns.response(201, "Banner inserted successfully")
-    @only_edition_cloud
-    @admin_required
-    def post(self):
-        payload = InsertExploreBannerPayload.model_validate(console_ns.payload)
-
-        banner = ExporleBanner(
-            content={
-                "category": payload.category,
-                "title": payload.title,
-                "description": payload.description,
-                "img-src": payload.img_src,
-            },
-            link=payload.link,
-            sort=payload.sort,
-            language=payload.language,
-        )
-        db.session.add(banner)
-        db.session.commit()
-
-        return {"result": "success"}, 201
-
-
-@console_ns.route("/admin/delete-explore-banner/<uuid:banner_id>")
-class DeleteExploreBannerApi(Resource):
-    @console_ns.doc("delete_explore_banner")
-    @console_ns.doc(description="Delete an explore banner")
-    @console_ns.doc(params={"banner_id": "Banner ID to delete"})
-    @console_ns.response(204, "Banner deleted successfully")
-    @only_edition_cloud
-    @admin_required
-    def delete(self, banner_id):
-        banner = db.session.execute(select(ExporleBanner).where(ExporleBanner.id == banner_id)).scalar_one_or_none()
-        if not banner:
-            raise NotFound(f"Banner '{banner_id}' is not found")
-
-        db.session.delete(banner)
-        db.session.commit()
-
-        return {"result": "success"}, 204
-
-
-class LangContentPayload(BaseModel):
-    lang: str = Field(..., description="Language tag: 'zh' | 'en' | 'jp'")
-    title: str = Field(...)
-    subtitle: str | None = Field(default=None)
-    body: str = Field(...)
-    title_pic_url: str | None = Field(default=None)
-
-
-class UpsertNotificationPayload(BaseModel):
-    notification_id: str | None = Field(default=None, description="Omit to create; supply UUID to update")
-    contents: list[LangContentPayload] = Field(..., min_length=1)
-    start_time: str | None = Field(default=None, description="RFC3339, e.g. 2026-03-01T00:00:00Z")
-    end_time: str | None = Field(default=None, description="RFC3339, e.g. 2026-03-20T23:59:59Z")
-    frequency: str = Field(default="once", description="'once' | 'every_page_load'")
-    status: str = Field(default="active", description="'active' | 'inactive'")
-
-
-class BatchAddNotificationAccountsPayload(BaseModel):
-    notification_id: str = Field(...)
-    user_email: list[str] = Field(..., description="List of account email addresses")
-
-
-register_schema_models(console_ns, UpsertNotificationPayload, BatchAddNotificationAccountsPayload)
-
-
-@console_ns.route("/admin/upsert_notification")
-class UpsertNotificationApi(Resource):
-    @console_ns.doc("upsert_notification")
-    @console_ns.doc(
-        description=(
-            "Create or update an in-product notification. "
-            "Supply notification_id to update an existing one; omit it to create a new one. "
-            "Pass at least one language variant in contents (zh / en / jp)."
-        )
-    )
-    @console_ns.expect(console_ns.models[UpsertNotificationPayload.__name__])
-    @console_ns.response(200, "Notification upserted successfully")
-    @only_edition_cloud
-    @admin_required
-    def post(self):
-        payload = UpsertNotificationPayload.model_validate(console_ns.payload)
-        result = BillingService.upsert_notification(
-            contents=[cast(LangContentDict, c.model_dump()) for c in payload.contents],
-            frequency=payload.frequency,
-            status=payload.status,
-            notification_id=payload.notification_id,
-            start_time=payload.start_time,
-            end_time=payload.end_time,
-        )
-        return {"result": "success", "notification_id": result.get("notificationId")}, 200
-
-
-@console_ns.route("/admin/batch_add_notification_accounts")
-class BatchAddNotificationAccountsApi(Resource):
-    @console_ns.doc("batch_add_notification_accounts")
-    @console_ns.doc(
-        description=(
-            "Register target accounts for a notification by email address. "
-            'JSON body: {"notification_id": "...", "user_email": ["a@example.com", ...]}. '
-            "File upload: multipart/form-data with a 'file' field (CSV or TXT, one email per line) "
-            "plus a 'notification_id' field. "
-            "Emails that do not match any account are silently skipped."
-        )
-    )
-    @console_ns.response(200, "Accounts added successfully")
-    @only_edition_cloud
-    @admin_required
-    def post(self):
-        from models.account import Account
-
-        if "file" in request.files:
-            notification_id = request.form.get("notification_id", "").strip()
-            if not notification_id:
-                raise BadRequest("notification_id is required.")
-            emails = self._parse_emails_from_file()
-        else:
-            payload = BatchAddNotificationAccountsPayload.model_validate(console_ns.payload)
-            notification_id = payload.notification_id
-            emails = payload.user_email
-
-        if not emails:
-            raise BadRequest("No valid email addresses provided.")
-
-        # Resolve emails → account IDs in chunks to avoid large IN-clause
-        account_ids: list[str] = []
-        chunk_size = 500
-        for i in range(0, len(emails), chunk_size):
-            chunk = emails[i : i + chunk_size]
-            rows = db.session.execute(select(Account.id, Account.email).where(Account.email.in_(chunk))).all()
-            account_ids.extend(str(row.id) for row in rows)
-
-        if not account_ids:
-            raise BadRequest("None of the provided emails matched an existing account.")
-
-        # Send to dify-saas in batches of 1000
-        total_count = 0
-        batch_size = 1000
-        for i in range(0, len(account_ids), batch_size):
-            batch = account_ids[i : i + batch_size]
-            result = BillingService.batch_add_notification_accounts(
-                notification_id=notification_id,
-                account_ids=batch,
-            )
-            total_count += result.get("count", 0)
-
-        return {
-            "result": "success",
-            "emails_provided": len(emails),
-            "accounts_matched": len(account_ids),
-            "count": total_count,
-        }, 200
-
-    @staticmethod
-    def _parse_emails_from_file() -> list[str]:
-        """Parse email addresses from an uploaded CSV or TXT file."""
-        file = request.files["file"]
-        if not file.filename:
-            raise BadRequest("Uploaded file has no filename.")
-
-        filename_lower = file.filename.lower()
-        if not filename_lower.endswith((".csv", ".txt")):
-            raise BadRequest("Invalid file type. Only CSV (.csv) and TXT (.txt) files are allowed.")
-
-        try:
-            content = file.stream.read().decode("utf-8")
-        except UnicodeDecodeError:
-            try:
-                file.stream.seek(0)
-                content = file.stream.read().decode("gbk")
-            except UnicodeDecodeError:
-                raise BadRequest("Unable to decode the file. Please use UTF-8 or GBK encoding.")
-
-        emails: list[str] = []
-        if filename_lower.endswith(".csv"):
-            reader = csv.reader(io.StringIO(content))
-            for row in reader:
-                for cell in row:
-                    cell = cell.strip()
-                    if cell:
-                        emails.append(cell)
-        else:
-            for line in content.splitlines():
-                line = line.strip()
-                if line:
-                    emails.append(line)
-
-        # Deduplicate while preserving order
-        seen: set[str] = set()
-        unique_emails: list[str] = []
-        for email in emails:
-            if email.lower() not in seen:
-                seen.add(email.lower())
-                unique_emails.append(email)
-
-        return unique_emails

api/controllers/console/apikey.py

@@ -11,6 +11,7 @@ from werkzeug.exceptions import Forbidden
 from controllers.common.schema import register_schema_models
 from extensions.ext_database import db
 from fields.base import ResponseModel
+from libs.helper import to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models.dataset import Dataset
 from models.enums import ApiTokenType
@@ -21,12 +22,6 @@ from . import console_ns
 from .wraps import account_initialization_required, edit_permission_required, setup_required
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 class ApiKeyItem(ResponseModel):
     id: str
     type: str
@@ -37,7 +32,7 @@ class ApiKeyItem(ResponseModel):
     @field_validator("last_used_at", "created_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class ApiKeyList(ResponseModel):

api/controllers/console/app/app.py

@@ -3,7 +3,6 @@ import re
 import uuid
 from datetime import datetime
 from typing import Any, Literal
-from uuid import UUID
 
 from flask import request
 from flask_restx import Resource
@@ -31,19 +30,16 @@ from core.ops.ops_trace_manager import OpsTraceManager
 from core.rag.entities import PreProcessingRule, Rule, Segmentation
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
 from core.trigger.constants import TRIGGER_NODE_TYPES
-from configs import dify_config
 from extensions.ext_database import db
 from fields.base import ResponseModel
 from graphon.enums import WorkflowExecutionStatus
-from libs.helper import build_icon_url
+from libs.helper import build_icon_url, to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models import App, DatasetPermissionEnum, Workflow
 from models.model import IconType
-from models.workflow import resolve_workflow_kind
 from services.app_dsl_service import AppDslService
 from services.app_service import AppListParams, AppService, CreateAppParams
 from services.enterprise.enterprise_service import EnterpriseService
-from services.enterprise import rbac_service as enterprise_rbac_service
 from services.entities.dsl_entities import ImportMode, ImportStatus
 from services.entities.knowledge_entities.knowledge_entities import (
     DataSource,
@@ -181,12 +177,6 @@ class AppTracePayload(BaseModel):
 type JSONValue = Any
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 class Tag(ResponseModel):
     id: str
     name: str
@@ -203,7 +193,7 @@ class WorkflowPartial(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class ModelConfigPartial(ResponseModel):
@@ -217,7 +207,7 @@ class ModelConfigPartial(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class ModelConfig(ResponseModel):
@@ -278,7 +268,7 @@ class ModelConfig(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class Site(ResponseModel):
@@ -321,7 +311,7 @@ class Site(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class DeletedTool(ResponseModel):
@@ -355,9 +345,6 @@ class AppPartial(ResponseModel):
     create_user_name: str | None = None
     author_name: str | None = None
     has_draft_trigger: bool | None = None
-    workflow_type: str | None = None
-    workflow_kind: str | None = None
-    permission_keys: list[str] = Field(default_factory=list)
 
     @computed_field(return_type=str | None)  # type: ignore
     @property
@@ -367,7 +354,7 @@ class AppPartial(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class AppDetail(ResponseModel):
@@ -392,15 +379,12 @@ class AppDetail(ResponseModel):
     updated_by: str | None = None
     updated_at: int | None = None
     access_mode: str | None = None
-    workflow_type: str | None = None
-    workflow_kind: str | None = None
     tags: list[Tag] = Field(default_factory=list)
-    permission_keys: list[str] = Field(default_factory=list)
 
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class AppDetailWithSite(AppDetail):
@@ -428,22 +412,6 @@ class AppExportResponse(ResponseModel):
     data: str
 
 
-def _collect_app_access_permission_keys(access_matrix: enterprise_rbac_service.AppAccessMatrix) -> list[str]:
-    permission_keys: list[str] = []
-    seen_permission_keys: set[str] = set()
-
-    for item in access_matrix.items:
-        if not item.policy:
-            continue
-        for permission_key in item.policy.permission_keys:
-            if permission_key in seen_permission_keys:
-                continue
-            seen_permission_keys.add(permission_key)
-            permission_keys.append(permission_key)
-
-    return permission_keys
-
-
 register_enum_models(console_ns, RetrievalMethod, WorkflowExecutionStatus, DatasetPermissionEnum)
 
 register_schema_models(
@@ -529,20 +497,6 @@ class AppListApi(Resource):
                 if str(app.id) in res:
                     app.access_mode = res[str(app.id)].access_mode
 
-        if app_pagination.items:
-            if dify_config.RBAC_ENABLED:
-                app_ids = [str(app.id) for app in app_pagination.items]
-                permission_keys_map = enterprise_rbac_service.RBACService.AppPermissions.batch_get(
-                    str(current_tenant_id),
-                    current_user.id,
-                    app_ids,
-                )
-                for app in app_pagination.items:
-                    app.permission_keys = permission_keys_map.get(str(app.id), [])
-            else:
-                for app in app_pagination.items:
-                    app.permission_keys = []
-
         workflow_capable_app_ids = [
             str(app.id) for app in app_pagination.items if app.mode in {"workflow", "advanced-chat"}
         ]
@@ -574,25 +528,6 @@ class AppListApi(Resource):
         for app in app_pagination.items:
             app.has_draft_trigger = str(app.id) in draft_trigger_app_ids
 
-        workflow_ids = [str(app.workflow_id) for app in app_pagination.items if app.workflow_id]
-        workflow_info_map: dict[str, tuple[str, str]] = {}
-        if workflow_ids:
-            rows = db.session.execute(
-                select(Workflow.id, Workflow.type, Workflow.kind).where(Workflow.id.in_(workflow_ids))
-            ).all()
-            workflow_info_map = {
-                str(row.id): (
-                    row.type.value if hasattr(row.type, "value") else str(row.type),
-                    resolve_workflow_kind(row.kind).value,
-                )
-                for row in rows
-            }
-
-        for app in app_pagination.items:
-            workflow_info = workflow_info_map.get(str(app.workflow_id)) if app.workflow_id else None
-            app.workflow_type = workflow_info[0] if workflow_info else None
-            app.workflow_kind = workflow_info[1] if workflow_info else None
-
         pagination_model = AppPagination.model_validate(app_pagination, from_attributes=True)
         return pagination_model.model_dump(mode="json"), 200
 
@@ -639,7 +574,6 @@ class AppApi(Resource):
     @get_app_model(mode=None)
     def get(self, app_model):
         """Get app detail"""
-        current_user, current_tenant_id = current_account_with_tenant()
         app_service = AppService()
 
         app_model = app_service.get_app(app_model)
@@ -648,29 +582,6 @@ class AppApi(Resource):
             app_setting = EnterpriseService.WebAppAuth.get_app_access_mode_by_id(app_id=str(app_model.id))
             app_model.access_mode = app_setting.access_mode
 
-
-        if app_model.workflow_id:
-            row = db.session.execute(
-                select(Workflow.type, Workflow.kind).where(Workflow.id == app_model.workflow_id)
-            ).first()
-            app_model.workflow_type = (
-                (row.type.value if hasattr(row.type, "value") else str(row.type)) if row else None
-            )
-            app_model.workflow_kind = resolve_workflow_kind(row.kind).value if row else None
-        else:
-            app_model.workflow_type = None
-            app_model.workflow_kind = None
-
-        if dify_config.RBAC_ENABLED:
-            app_access_matrix = enterprise_rbac_service.RBACService.AppAccess.matrix(
-                str(current_tenant_id),
-                current_user.id,
-                str(app_model.id),
-            )
-            app_model.permission_keys = _collect_app_access_permission_keys(app_access_matrix)
-        else:
-            app_model.permission_keys = []
-
         response_model = AppDetailWithSite.model_validate(app_model, from_attributes=True)
         return response_model.model_dump(mode="json")
 
@@ -938,10 +849,11 @@ class AppTraceApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id: UUID):
+    @get_app_model
+    def get(self, app_model):
         """Get app trace"""
         with session_factory.create_session() as session:
-            app_trace_config = OpsTraceManager.get_app_tracing_config(str(app_id), session)
+            app_trace_config = OpsTraceManager.get_app_tracing_config(app_model.id, session)
 
         return app_trace_config
 
@@ -955,12 +867,13 @@ class AppTraceApi(Resource):
     @login_required
     @account_initialization_required
     @edit_permission_required
-    def post(self, app_id: UUID):
+    @get_app_model
+    def post(self, app_model):
         # add app trace
         args = AppTracePayload.model_validate(console_ns.payload)
 
         OpsTraceManager.update_app_tracing_config(
-            app_id=str(app_id),
+            app_id=app_model.id,
             enabled=args.enabled,
             tracing_provider=args.tracing_provider,
         )

api/controllers/console/app/conversation_variables.py

@@ -16,6 +16,7 @@ from controllers.console.wraps import account_initialization_required, setup_req
 from extensions.ext_database import db
 from fields._value_type_serializer import serialize_value_type
 from fields.base import ResponseModel
+from libs.helper import to_timestamp
 from libs.login import login_required
 from models import ConversationVariable
 from models.model import AppMode
@@ -25,12 +26,6 @@ class ConversationVariablesQuery(BaseModel):
     conversation_id: str = Field(..., description="Conversation ID to filter variables")
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 class ConversationVariableResponse(ResponseModel):
     id: str
     name: str
@@ -65,7 +60,7 @@ class ConversationVariableResponse(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class PaginatedConversationVariableResponse(ResponseModel):

api/controllers/console/app/mcp_server.py

@@ -13,17 +13,12 @@ from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, edit_permission_required, setup_required
 from extensions.ext_database import db
 from fields.base import ResponseModel
+from libs.helper import to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models.enums import AppMCPServerStatus
 from models.model import AppMCPServer
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 class MCPServerCreatePayload(BaseModel):
     description: str | None = Field(default=None, description="Server description")
     parameters: dict[str, Any] = Field(..., description="Server parameters configuration")
@@ -41,14 +36,14 @@ class AppMCPServerResponse(ResponseModel):
     name: str
     server_code: str
     description: str
-    status: str
+    status: AppMCPServerStatus
     parameters: dict[str, Any] | list[Any] | str
     created_at: int | None = None
     updated_at: int | None = None
 
     @field_validator("parameters", mode="before")
     @classmethod
-    def _parse_json_string(cls, value: Any) -> Any:
+    def _normalize_parameters(cls, value: Any) -> Any:
         if isinstance(value, str):
             try:
                 return json.loads(value)
@@ -59,7 +54,7 @@ class AppMCPServerResponse(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 register_schema_models(console_ns, MCPServerCreatePayload, MCPServerUpdatePayload, AppMCPServerResponse)
@@ -70,7 +65,9 @@ class AppMCPServerController(Resource):
     @console_ns.doc("get_app_mcp_server")
     @console_ns.doc(description="Get MCP server configuration for an application")
     @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.response(200, "Server configuration", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(
+        200, "MCP server configuration retrieved successfully", console_ns.models[AppMCPServerResponse.__name__]
+    )
     @login_required
     @account_initialization_required
     @setup_required
@@ -85,7 +82,9 @@ class AppMCPServerController(Resource):
     @console_ns.doc(description="Create MCP server configuration for an application")
     @console_ns.doc(params={"app_id": "Application ID"})
     @console_ns.expect(console_ns.models[MCPServerCreatePayload.__name__])
-    @console_ns.response(200, "Server created", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(
+        201, "MCP server configuration created successfully", console_ns.models[AppMCPServerResponse.__name__]
+    )
     @console_ns.response(403, "Insufficient permissions")
     @account_initialization_required
     @get_app_model
@@ -111,13 +110,15 @@ class AppMCPServerController(Resource):
         )
         db.session.add(server)
         db.session.commit()
-        return AppMCPServerResponse.model_validate(server, from_attributes=True).model_dump(mode="json")
+        return AppMCPServerResponse.model_validate(server, from_attributes=True).model_dump(mode="json"), 201
 
     @console_ns.doc("update_app_mcp_server")
     @console_ns.doc(description="Update MCP server configuration for an application")
     @console_ns.doc(params={"app_id": "Application ID"})
     @console_ns.expect(console_ns.models[MCPServerUpdatePayload.__name__])
-    @console_ns.response(200, "Server updated", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(
+        200, "MCP server configuration updated successfully", console_ns.models[AppMCPServerResponse.__name__]
+    )
     @console_ns.response(403, "Insufficient permissions")
     @console_ns.response(404, "Server not found")
     @get_app_model
@@ -154,7 +155,7 @@ class AppMCPServerRefreshController(Resource):
     @console_ns.doc("refresh_app_mcp_server")
     @console_ns.doc(description="Refresh MCP server configuration and regenerate server code")
     @console_ns.doc(params={"server_id": "Server ID"})
-    @console_ns.response(200, "Server refreshed", console_ns.models[AppMCPServerResponse.__name__])
+    @console_ns.response(200, "MCP server refreshed successfully", console_ns.models[AppMCPServerResponse.__name__])
     @console_ns.response(403, "Insufficient permissions")
     @console_ns.response(404, "Server not found")
     @setup_required

api/controllers/console/app/message.py

@@ -37,10 +37,9 @@ from fields.conversation_fields import (
     JSONValue,
     MessageFile,
     format_files_contained,
-    to_timestamp,
 )
 from graphon.model_runtime.errors.invoke import InvokeError
-from libs.helper import uuid_value
+from libs.helper import to_timestamp, uuid_value
 from libs.infinite_scroll_pagination import InfiniteScrollPagination
 from libs.login import current_account_with_tenant, login_required
 from models.enums import FeedbackFromSource, FeedbackRating
@@ -144,9 +143,7 @@ class MessageDetailResponse(ResponseModel):
     @field_validator("created_at", mode="before")
     @classmethod
     def _normalize_created_at(cls, value: datetime | int | None) -> int | None:
-        if isinstance(value, datetime):
-            return to_timestamp(value)
-        return value
+        return to_timestamp(value)
 
 
 class MessageInfiniteScrollPaginationResponse(ResponseModel):

api/controllers/console/app/ops_trace.py

@@ -1,5 +1,4 @@
 from typing import Any
-from uuid import UUID
 
 from flask import request
 from flask_restx import Resource, fields
@@ -9,8 +8,10 @@ from werkzeug.exceptions import BadRequest
 from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.error import TracingConfigCheckError, TracingConfigIsExist, TracingConfigNotExist
+from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, setup_required
 from libs.login import login_required
+from models import App
 from services.ops_service import OpsService
 
 
@@ -43,11 +44,14 @@ class TraceAppConfigApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def get(self, app_id: UUID):
-        args = TraceProviderQuery.model_validate(request.args.to_dict(flat=True))
+    @get_app_model
+    def get(self, app_model: App):
+        args = TraceProviderQuery.model_validate(request.args.to_dict(flat=True))  # type: ignore
 
         try:
-            trace_config = OpsService.get_tracing_app_config(app_id=str(app_id), tracing_provider=args.tracing_provider)
+            trace_config = OpsService.get_tracing_app_config(
+                app_id=app_model.id, tracing_provider=args.tracing_provider
+            )
             if not trace_config:
                 return {"has_not_configured": True}
             return trace_config
@@ -65,13 +69,14 @@ class TraceAppConfigApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def post(self, app_id: UUID):
+    @get_app_model
+    def post(self, app_model: App):
         """Create a new trace app configuration"""
         args = TraceConfigPayload.model_validate(console_ns.payload)
 
         try:
             result = OpsService.create_tracing_app_config(
-                app_id=str(app_id), tracing_provider=args.tracing_provider, tracing_config=args.tracing_config
+                app_id=app_model.id, tracing_provider=args.tracing_provider, tracing_config=args.tracing_config
             )
             if not result:
                 raise TracingConfigIsExist()
@@ -90,13 +95,14 @@ class TraceAppConfigApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def patch(self, app_id: UUID):
+    @get_app_model
+    def patch(self, app_model: App):
         """Update an existing trace app configuration"""
         args = TraceConfigPayload.model_validate(console_ns.payload)
 
         try:
             result = OpsService.update_tracing_app_config(
-                app_id=str(app_id), tracing_provider=args.tracing_provider, tracing_config=args.tracing_config
+                app_id=app_model.id, tracing_provider=args.tracing_provider, tracing_config=args.tracing_config
             )
             if not result:
                 raise TracingConfigNotExist()
@@ -113,12 +119,13 @@ class TraceAppConfigApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    def delete(self, app_id: UUID):
+    @get_app_model
+    def delete(self, app_model: App):
         """Delete an existing trace app configuration"""
         args = TraceProviderQuery.model_validate(request.args.to_dict(flat=True))
 
         try:
-            result = OpsService.delete_tracing_app_config(app_id=str(app_id), tracing_provider=args.tracing_provider)
+            result = OpsService.delete_tracing_app_config(app_id=app_model.id, tracing_provider=args.tracing_provider)
             if not result:
                 raise TracingConfigNotExist()
             return {"result": "success"}, 204

api/controllers/console/app/workflow.py

@@ -1,21 +1,17 @@
 import json
 import logging
 from collections.abc import Sequence
-from typing import Any, Literal
+from typing import Any
 
 from flask import abort, request
 from flask_restx import Resource, fields, marshal, marshal_with
 from pydantic import BaseModel, Field, ValidationError, field_validator
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import sessionmaker
 from werkzeug.exceptions import BadRequest, Forbidden, InternalServerError, NotFound
 
 import services
 from controllers.common.controller_schemas import DefaultBlockConfigQuery, WorkflowListQuery, WorkflowUpdatePayload
-from controllers.common.schema import (
-    DEFAULT_REF_TEMPLATE_SWAGGER_2_0,
-    register_response_schema_model,
-    register_schema_models,
-)
+from controllers.common.schema import register_response_schema_model, register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.error import ConversationCompletedError, DraftWorkflowNotExist, DraftWorkflowNotSync
 from controllers.console.app.wraps import get_app_model
@@ -53,7 +49,7 @@ from libs.helper import TimestampField, uuid_value
 from libs.login import current_account_with_tenant, login_required
 from models import App
 from models.model import AppMode
-from models.workflow import Workflow, WorkflowKind
+from models.workflow import Workflow
 from repositories.workflow_collaboration_repository import WORKFLOW_ONLINE_USERS_PREFIX
 from services.app_generate_service import AppGenerateService
 from services.errors.app import IsDraftWorkflowError, WorkflowHashNotEqualError, WorkflowNotFoundError
@@ -161,23 +157,6 @@ class ConvertToWorkflowPayload(BaseModel):
     icon_background: str | None = None
 
 
-class WorkflowListQuery(BaseModel):
-    page: int = Field(default=1, ge=1, le=99999)
-    limit: int = Field(default=10, ge=1, le=100)
-    user_id: str | None = None
-    named_only: bool = False
-    keyword: str | None = Field(default=None, max_length=255)
-
-
-class WorkflowUpdatePayload(BaseModel):
-    marked_name: str | None = Field(default=None, max_length=20)
-    marked_comment: str | None = Field(default=None, max_length=100)
-
-
-class WorkflowTypeConvertQuery(BaseModel):
-    target_type: Literal["workflow", "evaluation"]
-
-
 class WorkflowFeaturesPayload(BaseModel):
     features: dict[str, Any] = Field(..., description="Workflow feature configuration")
 
@@ -199,26 +178,24 @@ class DraftWorkflowTriggerRunAllPayload(BaseModel):
     node_ids: list[str]
 
 
-def reg(cls: type[BaseModel]):
-    console_ns.schema_model(cls.__name__, cls.model_json_schema(ref_template=DEFAULT_REF_TEMPLATE_SWAGGER_2_0))
-
-
-reg(SyncDraftWorkflowPayload)
-reg(AdvancedChatWorkflowRunPayload)
-reg(IterationNodeRunPayload)
-reg(LoopNodeRunPayload)
-reg(DraftWorkflowRunPayload)
-reg(DraftWorkflowNodeRunPayload)
-reg(PublishWorkflowPayload)
-reg(DefaultBlockConfigQuery)
-reg(ConvertToWorkflowPayload)
-reg(WorkflowListQuery)
-reg(WorkflowUpdatePayload)
-reg(WorkflowTypeConvertQuery)
-reg(WorkflowFeaturesPayload)
-reg(WorkflowOnlineUsersPayload)
-reg(DraftWorkflowTriggerRunPayload)
-reg(DraftWorkflowTriggerRunAllPayload)
+register_schema_models(
+    console_ns,
+    SyncDraftWorkflowPayload,
+    AdvancedChatWorkflowRunPayload,
+    IterationNodeRunPayload,
+    LoopNodeRunPayload,
+    DraftWorkflowRunPayload,
+    DraftWorkflowNodeRunPayload,
+    PublishWorkflowPayload,
+    DefaultBlockConfigQuery,
+    ConvertToWorkflowPayload,
+    WorkflowListQuery,
+    WorkflowUpdatePayload,
+    WorkflowFeaturesPayload,
+    WorkflowOnlineUsersPayload,
+    DraftWorkflowTriggerRunPayload,
+    DraftWorkflowTriggerRunAllPayload,
+)
 register_response_schema_model(console_ns, WorkflowRunNodeExecutionResponse)
 
 
@@ -898,54 +875,6 @@ class PublishedWorkflowApi(Resource):
         }
 
 
-@console_ns.route("/apps/<uuid:app_id>/workflows/publish/evaluation")
-class EvaluationPublishedWorkflowApi(Resource):
-    @console_ns.doc("publish_evaluation_workflow")
-    @console_ns.doc(description="Publish draft workflow as evaluation workflow")
-    @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.expect(console_ns.models[PublishWorkflowPayload.__name__])
-    @console_ns.response(200, "Evaluation workflow published successfully")
-    @console_ns.response(400, "Invalid workflow or unsupported node type")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
-    @edit_permission_required
-    def post(self, app_model: App):
-        """
-        Publish draft workflow as evaluation workflow.
-
-        Evaluation workflows cannot include trigger or human-input nodes.
-        """
-        current_user, _ = current_account_with_tenant()
-        args = PublishWorkflowPayload.model_validate(console_ns.payload or {})
-
-        workflow_service = WorkflowService()
-        with Session(db.engine, expire_on_commit=False) as session:
-            workflow = workflow_service.publish_evaluation_workflow(
-                session=session,
-                app_model=app_model,
-                account=current_user,
-                marked_name=args.marked_name or "",
-                marked_comment=args.marked_comment or "",
-            )
-
-            # Keep workflow_id aligned with the latest published workflow.
-            app_model_in_session = session.get(App, app_model.id)
-            if app_model_in_session:
-                app_model_in_session.workflow_id = workflow.id
-                app_model_in_session.updated_by = current_user.id
-                app_model_in_session.updated_at = naive_utc_now()
-
-            workflow_created_at = TimestampField().format(workflow.created_at)
-            session.commit()
-
-        return {
-            "result": "success",
-            "created_at": workflow_created_at,
-        }
-
-
 @console_ns.route("/apps/<uuid:app_id>/workflows/default-workflow-block-configs")
 class DefaultBlockConfigsApi(Resource):
     @console_ns.doc("get_default_block_configs")
@@ -1143,52 +1072,6 @@ class DraftWorkflowRestoreApi(Resource):
         }
 
 
-@console_ns.route("/apps/<uuid:app_id>/workflows/convert-type")
-class WorkflowTypeConvertApi(Resource):
-    @console_ns.doc("convert_published_workflow_type")
-    @console_ns.doc(description="Convert current effective published workflow type in-place")
-    @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.expect(console_ns.models[WorkflowTypeConvertQuery.__name__])
-    @console_ns.response(200, "Workflow type converted successfully")
-    @console_ns.response(400, "Invalid workflow type or unsupported workflow graph")
-    @console_ns.response(404, "Workflow not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_app_model(mode=[AppMode.ADVANCED_CHAT, AppMode.WORKFLOW])
-    @edit_permission_required
-    def post(self, app_model: App):
-        current_user, _ = current_account_with_tenant()
-        args = WorkflowTypeConvertQuery.model_validate(request.args.to_dict(flat=True))  # type: ignore
-        target_type = WorkflowKind.EVALUATION if args.target_type == "evaluation" else WorkflowKind.STANDARD
-
-        workflow_service = WorkflowService()
-        with Session(db.engine, expire_on_commit=False) as session:
-            try:
-                workflow = workflow_service.convert_published_workflow_type(
-                    session=session,
-                    app_model=app_model,
-                    target_type=target_type,
-                    account=current_user,
-                )
-            except WorkflowNotFoundError as exc:
-                raise NotFound(str(exc)) from exc
-            except IsDraftWorkflowError as exc:
-                raise BadRequest(str(exc)) from exc
-            except ValueError as exc:
-                raise BadRequest(str(exc)) from exc
-
-            session.commit()
-
-        return {
-            "result": "success",
-            "workflow_id": workflow.id,
-            "type": workflow.type.value,
-            "kind": workflow.kind_or_standard,
-            "updated_at": TimestampField().format(workflow.updated_at or workflow.created_at),
-        }
-
-
 @console_ns.route("/apps/<uuid:app_id>/workflows/<string:workflow_id>")
 class WorkflowByIdApi(Resource):
     @console_ns.doc("update_workflow_by_id")

api/controllers/console/app/workflow_app_log.py

@@ -16,6 +16,7 @@ from fields.base import ResponseModel
 from fields.end_user_fields import SimpleEndUser
 from fields.member_fields import SimpleAccount
 from graphon.enums import WorkflowExecutionStatus
+from libs.helper import to_timestamp
 from libs.login import login_required
 from models import App
 from models.model import AppMode
@@ -82,9 +83,7 @@ class WorkflowRunForLogResponse(ResponseModel):
     @field_validator("created_at", "finished_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        if isinstance(value, datetime):
-            return int(value.timestamp())
-        return value
+        return to_timestamp(value)
 
 
 class WorkflowRunForArchivedLogResponse(ResponseModel):
@@ -104,28 +103,10 @@ class WorkflowRunForArchivedLogResponse(ResponseModel):
         return str(getattr(value, "value", value))
 
 
-class WorkflowAppLogEvaluationNodeInfoResponse(ResponseModel):
-    node_id: str
-    type: str
-    title: str
-
-
-class WorkflowAppLogEvaluationItemResponse(ResponseModel):
-    name: str
-    value: Any = None
-    details: dict[str, Any] | None = None
-    node_info: WorkflowAppLogEvaluationNodeInfoResponse | None = Field(
-        default=None,
-        validation_alias="node_info",
-        serialization_alias="nodeInfo",
-    )
-
-
 class WorkflowAppLogPartialResponse(ResponseModel):
     id: str
     workflow_run: WorkflowRunForLogResponse | None = None
     details: Any = None
-    evaluation: list[WorkflowAppLogEvaluationItemResponse] = Field(default_factory=list)
     created_from: str | None = None
     created_by_role: str | None = None
     created_by_account: SimpleAccount | None = None
@@ -135,14 +116,7 @@ class WorkflowAppLogPartialResponse(ResponseModel):
     @field_validator("created_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        if isinstance(value, datetime):
-            return int(value.timestamp())
-        return value
-
-    @field_validator("evaluation", mode="before")
-    @classmethod
-    def _normalize_evaluation(cls, value: Any) -> list[dict[str, Any]] | list[WorkflowAppLogEvaluationItemResponse]:
-        return value or []
+        return to_timestamp(value)
 
 
 class WorkflowArchivedLogPartialResponse(ResponseModel):
@@ -156,9 +130,7 @@ class WorkflowArchivedLogPartialResponse(ResponseModel):
     @field_validator("created_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        if isinstance(value, datetime):
-            return int(value.timestamp())
-        return value
+        return to_timestamp(value)
 
 
 class WorkflowAppLogPaginationResponse(ResponseModel):
@@ -182,8 +154,6 @@ register_schema_models(
     WorkflowAppLogQuery,
     WorkflowRunForLogResponse,
     WorkflowRunForArchivedLogResponse,
-    WorkflowAppLogEvaluationNodeInfoResponse,
-    WorkflowAppLogEvaluationItemResponse,
     WorkflowAppLogPartialResponse,
     WorkflowArchivedLogPartialResponse,
     WorkflowAppLogPaginationResponse,

api/controllers/console/app/workflow_comment.py

@@ -1,22 +1,16 @@
 import logging
+from datetime import datetime
 
-from flask_restx import Resource, marshal_with
-from pydantic import BaseModel, Field, TypeAdapter
+from flask_restx import Resource
+from pydantic import BaseModel, Field, TypeAdapter, computed_field, field_validator
 
-from controllers.common.schema import register_schema_models
+from controllers.common.schema import register_response_schema_models, register_schema_models
 from controllers.console import console_ns
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, edit_permission_required, setup_required
+from fields.base import ResponseModel
 from fields.member_fields import AccountWithRole
-from fields.workflow_comment_fields import (
-    workflow_comment_basic_fields,
-    workflow_comment_create_fields,
-    workflow_comment_detail_fields,
-    workflow_comment_reply_create_fields,
-    workflow_comment_reply_update_fields,
-    workflow_comment_resolve_fields,
-    workflow_comment_update_fields,
-)
+from libs.helper import build_avatar_url, dump_response, to_timestamp
 from libs.login import current_user, login_required
 from models import App
 from services.account_service import TenantService
@@ -51,6 +45,138 @@ class WorkflowCommentMentionUsersPayload(BaseModel):
     users: list[AccountWithRole]
 
 
+class WorkflowCommentAccount(ResponseModel):
+    id: str
+    name: str
+    email: str
+    avatar: str | None = Field(default=None, exclude=True)
+
+    @computed_field(return_type=str | None)  # type: ignore[prop-decorator]
+    @property
+    def avatar_url(self) -> str | None:
+        return build_avatar_url(self.avatar)
+
+
+class WorkflowCommentReply(ResponseModel):
+    id: str
+    content: str
+    created_by: str
+    created_by_account: WorkflowCommentAccount | None = None
+    created_at: int | None = None
+
+    @field_validator("created_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class WorkflowCommentMention(ResponseModel):
+    mentioned_user_id: str
+    mentioned_user_account: WorkflowCommentAccount | None = None
+    reply_id: str | None = None
+
+
+class WorkflowCommentBasic(ResponseModel):
+    id: str
+    position_x: float
+    position_y: float
+    content: str
+    created_by: str
+    created_by_account: WorkflowCommentAccount | None = None
+    created_at: int | None = None
+    updated_at: int | None = None
+    resolved: bool
+    resolved_at: int | None = None
+    resolved_by: str | None = None
+    resolved_by_account: WorkflowCommentAccount | None = None
+    reply_count: int
+    mention_count: int
+    participants: list[WorkflowCommentAccount]
+
+    @field_validator("created_at", "updated_at", "resolved_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class WorkflowCommentBasicList(ResponseModel):
+    data: list[WorkflowCommentBasic]
+
+
+class WorkflowCommentDetail(ResponseModel):
+    id: str
+    position_x: float
+    position_y: float
+    content: str
+    created_by: str
+    created_by_account: WorkflowCommentAccount | None = None
+    created_at: int | None = None
+    updated_at: int | None = None
+    resolved: bool
+    resolved_at: int | None = None
+    resolved_by: str | None = None
+    resolved_by_account: WorkflowCommentAccount | None = None
+    replies: list[WorkflowCommentReply]
+    mentions: list[WorkflowCommentMention]
+
+    @field_validator("created_at", "updated_at", "resolved_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class WorkflowCommentCreate(ResponseModel):
+    id: str
+    created_at: int | None = None
+
+    @field_validator("created_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class WorkflowCommentUpdate(ResponseModel):
+    id: str
+    updated_at: int | None = None
+
+    @field_validator("updated_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class WorkflowCommentResolve(ResponseModel):
+    id: str
+    resolved: bool
+    resolved_at: int | None = None
+    resolved_by: str | None = None
+
+    @field_validator("resolved_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class WorkflowCommentReplyCreate(ResponseModel):
+    id: str
+    created_at: int | None = None
+
+    @field_validator("created_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class WorkflowCommentReplyUpdate(ResponseModel):
+    id: str
+    updated_at: int | None = None
+
+    @field_validator("updated_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
 register_schema_models(
     console_ns,
     AccountWithRole,
@@ -59,17 +185,19 @@ register_schema_models(
     WorkflowCommentUpdatePayload,
     WorkflowCommentReplyPayload,
 )
-
-workflow_comment_basic_model = console_ns.model("WorkflowCommentBasic", workflow_comment_basic_fields)
-workflow_comment_detail_model = console_ns.model("WorkflowCommentDetail", workflow_comment_detail_fields)
-workflow_comment_create_model = console_ns.model("WorkflowCommentCreate", workflow_comment_create_fields)
-workflow_comment_update_model = console_ns.model("WorkflowCommentUpdate", workflow_comment_update_fields)
-workflow_comment_resolve_model = console_ns.model("WorkflowCommentResolve", workflow_comment_resolve_fields)
-workflow_comment_reply_create_model = console_ns.model(
-    "WorkflowCommentReplyCreate", workflow_comment_reply_create_fields
-)
-workflow_comment_reply_update_model = console_ns.model(
-    "WorkflowCommentReplyUpdate", workflow_comment_reply_update_fields
+register_response_schema_models(
+    console_ns,
+    WorkflowCommentAccount,
+    WorkflowCommentReply,
+    WorkflowCommentMention,
+    WorkflowCommentBasic,
+    WorkflowCommentBasicList,
+    WorkflowCommentDetail,
+    WorkflowCommentCreate,
+    WorkflowCommentUpdate,
+    WorkflowCommentResolve,
+    WorkflowCommentReplyCreate,
+    WorkflowCommentReplyUpdate,
 )
 
 
@@ -80,28 +208,26 @@ class WorkflowCommentListApi(Resource):
     @console_ns.doc("list_workflow_comments")
     @console_ns.doc(description="Get all comments for a workflow")
     @console_ns.doc(params={"app_id": "Application ID"})
-    @console_ns.response(200, "Comments retrieved successfully", workflow_comment_basic_model)
+    @console_ns.response(200, "Comments retrieved successfully", console_ns.models[WorkflowCommentBasicList.__name__])
     @login_required
     @setup_required
     @account_initialization_required
     @get_app_model()
-    @marshal_with(workflow_comment_basic_model, envelope="data")
     def get(self, app_model: App):
         """Get all comments for a workflow."""
         comments = WorkflowCommentService.get_comments(tenant_id=current_user.current_tenant_id, app_id=app_model.id)
 
-        return comments
+        return WorkflowCommentBasicList.model_validate({"data": comments}).model_dump(mode="json")
 
     @console_ns.doc("create_workflow_comment")
     @console_ns.doc(description="Create a new workflow comment")
     @console_ns.doc(params={"app_id": "Application ID"})
     @console_ns.expect(console_ns.models[WorkflowCommentCreatePayload.__name__])
-    @console_ns.response(201, "Comment created successfully", workflow_comment_create_model)
+    @console_ns.response(201, "Comment created successfully", console_ns.models[WorkflowCommentCreate.__name__])
     @login_required
     @setup_required
     @account_initialization_required
     @get_app_model()
-    @marshal_with(workflow_comment_create_model)
     @edit_permission_required
     def post(self, app_model: App):
         """Create a new workflow comment."""
@@ -117,7 +243,7 @@ class WorkflowCommentListApi(Resource):
             mentioned_user_ids=payload.mentioned_user_ids,
         )
 
-        return result, 201
+        return dump_response(WorkflowCommentCreate, result), 201
 
 
 @console_ns.route("/apps/<uuid:app_id>/workflow/comments/<string:comment_id>")
@@ -127,30 +253,28 @@ class WorkflowCommentDetailApi(Resource):
     @console_ns.doc("get_workflow_comment")
     @console_ns.doc(description="Get a specific workflow comment")
     @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
-    @console_ns.response(200, "Comment retrieved successfully", workflow_comment_detail_model)
+    @console_ns.response(200, "Comment retrieved successfully", console_ns.models[WorkflowCommentDetail.__name__])
     @login_required
     @setup_required
     @account_initialization_required
     @get_app_model()
-    @marshal_with(workflow_comment_detail_model)
     def get(self, app_model: App, comment_id: str):
         """Get a specific workflow comment."""
         comment = WorkflowCommentService.get_comment(
             tenant_id=current_user.current_tenant_id, app_id=app_model.id, comment_id=comment_id
         )
 
-        return comment
+        return dump_response(WorkflowCommentDetail, comment)
 
     @console_ns.doc("update_workflow_comment")
     @console_ns.doc(description="Update a workflow comment")
     @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
     @console_ns.expect(console_ns.models[WorkflowCommentUpdatePayload.__name__])
-    @console_ns.response(200, "Comment updated successfully", workflow_comment_update_model)
+    @console_ns.response(200, "Comment updated successfully", console_ns.models[WorkflowCommentUpdate.__name__])
     @login_required
     @setup_required
     @account_initialization_required
     @get_app_model()
-    @marshal_with(workflow_comment_update_model)
     @edit_permission_required
     def put(self, app_model: App, comment_id: str):
         """Update a workflow comment."""
@@ -167,7 +291,7 @@ class WorkflowCommentDetailApi(Resource):
             mentioned_user_ids=payload.mentioned_user_ids,
         )
 
-        return result
+        return dump_response(WorkflowCommentUpdate, result)
 
     @console_ns.doc("delete_workflow_comment")
     @console_ns.doc(description="Delete a workflow comment")
@@ -197,12 +321,11 @@ class WorkflowCommentResolveApi(Resource):
     @console_ns.doc("resolve_workflow_comment")
     @console_ns.doc(description="Resolve a workflow comment")
     @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
-    @console_ns.response(200, "Comment resolved successfully", workflow_comment_resolve_model)
+    @console_ns.response(200, "Comment resolved successfully", console_ns.models[WorkflowCommentResolve.__name__])
     @login_required
     @setup_required
     @account_initialization_required
     @get_app_model()
-    @marshal_with(workflow_comment_resolve_model)
     @edit_permission_required
     def post(self, app_model: App, comment_id: str):
         """Resolve a workflow comment."""
@@ -213,7 +336,7 @@ class WorkflowCommentResolveApi(Resource):
             user_id=current_user.id,
         )
 
-        return comment
+        return dump_response(WorkflowCommentResolve, comment)
 
 
 @console_ns.route("/apps/<uuid:app_id>/workflow/comments/<string:comment_id>/replies")
@@ -224,12 +347,11 @@ class WorkflowCommentReplyApi(Resource):
     @console_ns.doc(description="Add a reply to a workflow comment")
     @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID"})
     @console_ns.expect(console_ns.models[WorkflowCommentReplyPayload.__name__])
-    @console_ns.response(201, "Reply created successfully", workflow_comment_reply_create_model)
+    @console_ns.response(201, "Reply created successfully", console_ns.models[WorkflowCommentReplyCreate.__name__])
     @login_required
     @setup_required
     @account_initialization_required
     @get_app_model()
-    @marshal_with(workflow_comment_reply_create_model)
     @edit_permission_required
     def post(self, app_model: App, comment_id: str):
         """Add a reply to a workflow comment."""
@@ -247,7 +369,7 @@ class WorkflowCommentReplyApi(Resource):
             mentioned_user_ids=payload.mentioned_user_ids,
         )
 
-        return result, 201
+        return dump_response(WorkflowCommentReplyCreate, result), 201
 
 
 @console_ns.route("/apps/<uuid:app_id>/workflow/comments/<string:comment_id>/replies/<string:reply_id>")
@@ -258,12 +380,11 @@ class WorkflowCommentReplyDetailApi(Resource):
     @console_ns.doc(description="Update a comment reply")
     @console_ns.doc(params={"app_id": "Application ID", "comment_id": "Comment ID", "reply_id": "Reply ID"})
     @console_ns.expect(console_ns.models[WorkflowCommentReplyPayload.__name__])
-    @console_ns.response(200, "Reply updated successfully", workflow_comment_reply_update_model)
+    @console_ns.response(200, "Reply updated successfully", console_ns.models[WorkflowCommentReplyUpdate.__name__])
     @login_required
     @setup_required
     @account_initialization_required
     @get_app_model()
-    @marshal_with(workflow_comment_reply_update_model)
     @edit_permission_required
     def put(self, app_model: App, comment_id: str, reply_id: str):
         """Update a comment reply."""
@@ -284,7 +405,7 @@ class WorkflowCommentReplyDetailApi(Resource):
             mentioned_user_ids=payload.mentioned_user_ids,
         )
 
-        return reply
+        return dump_response(WorkflowCommentReplyUpdate, reply)
 
     @console_ns.doc("delete_workflow_comment_reply")
     @console_ns.doc(description="Delete a comment reply")

api/controllers/console/billing/billing.py

@@ -1,6 +1,4 @@
 import base64
-import json
-from datetime import UTC, datetime, timedelta
 from typing import Literal
 
 from flask import request
@@ -12,7 +10,6 @@ from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from controllers.console.wraps import account_initialization_required, only_edition_cloud, setup_required
 from enums.cloud_plan import CloudPlan
-from extensions.ext_redis import redis_client
 from libs.login import current_account_with_tenant, login_required
 from services.billing_service import BillingService
 
@@ -80,39 +77,3 @@ class PartnerTenants(Resource):
             raise BadRequest("Invalid partner information")
 
         return BillingService.sync_partner_tenants_bindings(current_user.id, decoded_partner_key, click_id)
-
-
-_DEBUG_KEY = "billing:debug"
-_DEBUG_TTL = timedelta(days=7)
-
-
-class DebugDataPayload(BaseModel):
-    type: str = Field(..., min_length=1, description="Data type key")
-    data: str = Field(..., min_length=1, description="Data value to append")
-
-
-@console_ns.route("/billing/debug/data")
-class DebugData(Resource):
-    def post(self):
-        body = DebugDataPayload.model_validate(request.get_json(force=True))
-        item = json.dumps({
-            "type": body.type,
-            "data": body.data,
-            "createTime": datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ"),
-        })
-        redis_client.lpush(_DEBUG_KEY, item)
-        redis_client.expire(_DEBUG_KEY, _DEBUG_TTL)
-        return {"result": "ok"}, 201
-
-    def get(self):
-        recent = request.args.get("recent", 10, type=int)
-        items = redis_client.lrange(_DEBUG_KEY, 0, recent - 1)
-        return {
-            "data": [
-                json.loads(item.decode("utf-8") if isinstance(item, bytes) else item) for item in items
-            ]
-        }
-
-    def delete(self):
-        redis_client.delete(_DEBUG_KEY)
-        return {"result": "ok"}

api/controllers/console/datasets/datasets.py

@@ -1,13 +1,10 @@
-import json
 from typing import Any, cast
-from urllib.parse import quote
 
-from flask import Response, request
+from flask import request
 from flask_restx import Resource, fields, marshal, marshal_with
 from pydantic import BaseModel, Field, field_validator
 from sqlalchemy import func, select
-from sqlalchemy.orm import Session
-from werkzeug.exceptions import BadRequest, Forbidden, NotFound
+from werkzeug.exceptions import Forbidden, NotFound
 
 import services
 from configs import dify_config
@@ -24,7 +21,6 @@ from controllers.console.wraps import (
     setup_required,
 )
 from core.errors.error import LLMBadRequestError, ProviderTokenNotInitError
-from core.evaluation.entities.evaluation_entity import EvaluationCategory, EvaluationConfigData, EvaluationRunRequest
 from core.indexing_runner import IndexingRunner
 from core.plugin.impl.model_runtime_factory import create_plugin_provider_manager
 from core.rag.datasource.vdb.vector_type import VectorType
@@ -33,7 +29,6 @@ from core.rag.extractor.entity.extract_setting import ExtractSetting, NotionInfo
 from core.rag.index_processor.constant.index_type import IndexTechniqueType
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
 from extensions.ext_database import db
-from extensions.ext_storage import storage
 from fields.app_fields import app_detail_kernel_fields, related_app_list
 from fields.dataset_fields import (
     content_fields,
@@ -56,22 +51,13 @@ from fields.document_fields import document_status_fields
 from graphon.model_runtime.entities.model_entities import ModelType
 from libs.login import current_account_with_tenant, login_required
 from libs.url_utils import normalize_api_base_url
-from models import ApiToken, Dataset, Document, DocumentSegment, EvaluationRun, EvaluationTargetType, UploadFile
+from models import ApiToken, Dataset, Document, DocumentSegment, UploadFile
 from models.dataset import DatasetPermission, DatasetPermissionEnum
 from models.enums import ApiTokenType, SegmentStatus
 from models.provider_ids import ModelProviderID
 from services.api_token_service import ApiTokenCache
 from services.dataset_service import DatasetPermissionService, DatasetService, DocumentService
 
-from services.errors.evaluation import (
-    EvaluationDatasetInvalidError,
-    EvaluationFrameworkNotConfiguredError,
-    EvaluationMaxConcurrentRunsError,
-    EvaluationNotFoundError,
-)
-from services.evaluation_service import EvaluationService
-from services.enterprise import rbac_service as enterprise_rbac_service
-
 # Register models for flask_restx to avoid dict type issues in Swagger
 dataset_base_model = get_or_create_model("DatasetBase", dataset_fields)
 
@@ -141,14 +127,6 @@ def _validate_doc_form(value: str | None) -> str | None:
     return value
 
 
-def _ensure_permission_keys(dataset: Dataset, *, enabled: bool) -> None:
-    if not enabled:
-        setattr(dataset, "permission_keys", [])
-        return
-    if not isinstance(getattr(dataset, "permission_keys", None), list):
-        setattr(dataset, "permission_keys", [])
-
-
 class DatasetCreatePayload(BaseModel):
     name: str = Field(..., min_length=1, max_length=40)
     description: str = Field("", max_length=400)
@@ -351,19 +329,6 @@ class DatasetListApi(Resource):
                 query.include_all,
             )
 
-        for dataset in datasets:
-            _ensure_permission_keys(dataset, enabled=dify_config.RBAC_ENABLED)
-
-        if dify_config.RBAC_ENABLED and datasets:
-            dataset_ids = [str(dataset.id) for dataset in datasets]
-            permission_keys_map = enterprise_rbac_service.RBACService.DatasetPermissions.batch_get(
-                str(current_tenant_id),
-                current_user.id,
-                dataset_ids,
-            )
-            for dataset in datasets:
-                setattr(dataset, "permission_keys", permission_keys_map.get(str(dataset.id), []))
-
         # check embedding setting
         provider_manager = create_plugin_provider_manager(tenant_id=current_tenant_id)
         configurations = provider_manager.get_configurations(tenant_id=current_tenant_id)
@@ -445,7 +410,6 @@ class DatasetListApi(Resource):
         except services.errors.dataset.DatasetNameDuplicateError:
             raise DatasetNameDuplicateError()
 
-        _ensure_permission_keys(dataset, enabled=dify_config.RBAC_ENABLED)
         return marshal(dataset, dataset_detail_fields), 201
 
 
@@ -470,7 +434,6 @@ class DatasetApi(Resource):
             DatasetService.check_dataset_permission(dataset, current_user)
         except services.errors.account.NoPermissionError as e:
             raise Forbidden(str(e))
-        _ensure_permission_keys(dataset, enabled=dify_config.RBAC_ENABLED)
         data = cast(dict[str, Any], marshal(dataset, dataset_detail_fields))
         if dataset.indexing_technique == IndexTechniqueType.HIGH_QUALITY:
             if dataset.embedding_model_provider:
@@ -540,7 +503,6 @@ class DatasetApi(Resource):
         if dataset is None:
             raise NotFound("Dataset not found.")
 
-        _ensure_permission_keys(dataset, enabled=dify_config.RBAC_ENABLED)
         result_data = cast(dict[str, Any], marshal(dataset, dataset_detail_fields))
         tenant_id = current_tenant_id
 
@@ -1023,432 +985,3 @@ class DatasetAutoDisableLogApi(Resource):
         if dataset is None:
             raise NotFound("Dataset not found.")
         return DatasetService.get_dataset_auto_disable_logs(dataset_id_str), 200
-
-
-# ---- Knowledge Base Retrieval Evaluation ----
-
-
-def _serialize_dataset_evaluation_run(run: EvaluationRun) -> dict[str, Any]:
-    return {
-        "id": run.id,
-        "tenant_id": run.tenant_id,
-        "target_type": run.target_type,
-        "target_id": run.target_id,
-        "evaluation_config_id": run.evaluation_config_id,
-        "status": run.status,
-        "dataset_file_id": run.dataset_file_id,
-        "result_file_id": run.result_file_id,
-        "total_items": run.total_items,
-        "completed_items": run.completed_items,
-        "failed_items": run.failed_items,
-        "progress": run.progress,
-        "metrics_summary": json.loads(run.metrics_summary) if run.metrics_summary else {},
-        "error": run.error,
-        "created_by": run.created_by,
-        "started_at": int(run.started_at.timestamp()) if run.started_at else None,
-        "completed_at": int(run.completed_at.timestamp()) if run.completed_at else None,
-        "created_at": int(run.created_at.timestamp()) if run.created_at else None,
-    }
-
-
-def _serialize_dataset_evaluation_run_item(item: Any) -> dict[str, Any]:
-    return {
-        "id": item.id,
-        "item_index": item.item_index,
-        "inputs": item.inputs_dict,
-        "expected_output": item.expected_output,
-        "actual_output": item.actual_output,
-        "metrics": item.metrics_list,
-        "judgment": item.judgment_dict,
-        "metadata": item.metadata_dict,
-        "error": item.error,
-        "overall_score": item.overall_score,
-    }
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation/template/download")
-class DatasetEvaluationTemplateDownloadApi(Resource):
-    @console_ns.doc("download_dataset_evaluation_template")
-    @console_ns.response(200, "Template file streamed as XLSX attachment")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def post(self, dataset_id):
-        """Download evaluation dataset template for knowledge base retrieval."""
-        current_user, _ = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        xlsx_content, filename = EvaluationService.generate_retrieval_dataset_template()
-        encoded_filename = quote(filename)
-        response = Response(
-            xlsx_content,
-            mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
-        )
-        response.headers["Content-Disposition"] = f"attachment; filename*=UTF-8''{encoded_filename}"
-        response.headers["Content-Length"] = str(len(xlsx_content))
-        return response
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation")
-class DatasetEvaluationDetailApi(Resource):
-    @console_ns.doc("get_dataset_evaluation_config")
-    @console_ns.response(200, "Evaluation configuration retrieved")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self, dataset_id):
-        """Get evaluation configuration for the knowledge base."""
-        current_user, current_tenant_id = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        with Session(db.engine, expire_on_commit=False) as session:
-            config = EvaluationService.get_evaluation_config(
-                session, current_tenant_id, "dataset", dataset_id_str
-            )
-
-        if config is None:
-            return {
-                "evaluation_model": None,
-                "evaluation_model_provider": None,
-                "default_metrics": None,
-                "customized_metrics": None,
-                "judgment_config": None,
-            }
-
-        return {
-            "evaluation_model": config.evaluation_model,
-            "evaluation_model_provider": config.evaluation_model_provider,
-            "default_metrics": config.default_metrics_list,
-            "customized_metrics": config.customized_metrics_dict,
-            "judgment_config": config.judgment_config_dict,
-        }
-
-    @console_ns.doc("save_dataset_evaluation_config")
-    @console_ns.response(200, "Evaluation configuration saved")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def put(self, dataset_id):
-        """Save evaluation configuration for the knowledge base."""
-        current_user, current_tenant_id = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        body = request.get_json(force=True)
-        try:
-            config_data = EvaluationConfigData.model_validate(body)
-        except Exception as e:
-            raise BadRequest(f"Invalid request body: {e}")
-
-        with Session(db.engine, expire_on_commit=False) as session:
-            config = EvaluationService.save_evaluation_config(
-                session=session,
-                tenant_id=current_tenant_id,
-                target_type="dataset",
-                target_id=dataset_id_str,
-                account_id=str(current_user.id),
-                data=config_data,
-            )
-
-        return {
-            "evaluation_model": config.evaluation_model,
-            "evaluation_model_provider": config.evaluation_model_provider,
-            "default_metrics": config.default_metrics_list,
-            "customized_metrics": config.customized_metrics_dict,
-            "judgment_config": config.judgment_config_dict,
-        }
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation/run")
-class DatasetEvaluationRunApi(Resource):
-    @console_ns.doc("start_dataset_evaluation_run")
-    @console_ns.response(200, "Evaluation run started")
-    @console_ns.response(400, "Invalid request")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def post(self, dataset_id):
-        """Start an evaluation run for the knowledge base retrieval."""
-        current_user, current_tenant_id = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        body = request.get_json(force=True)
-        if not body:
-            raise BadRequest("Request body is required.")
-
-        try:
-            run_request = EvaluationRunRequest.model_validate(body)
-        except Exception as e:
-            raise BadRequest(f"Invalid request body: {e}")
-
-        upload_file = (
-            db.session.query(UploadFile).filter_by(id=run_request.file_id, tenant_id=current_tenant_id).first()
-        )
-        if not upload_file:
-            raise NotFound("Dataset file not found.")
-
-        try:
-            dataset_content = storage.load_once(upload_file.key)
-        except Exception:
-            raise BadRequest("Failed to read dataset file.")
-
-        if not dataset_content:
-            raise BadRequest("Dataset file is empty.")
-
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                evaluation_run = EvaluationService.start_evaluation_run(
-                    session=session,
-                    tenant_id=current_tenant_id,
-                    target_type=EvaluationTargetType.KNOWLEDGE_BASE,
-                    target_id=dataset_id_str,
-                    account_id=str(current_user.id),
-                    dataset_file_content=dataset_content,
-                    run_request=run_request,
-                )
-                return _serialize_dataset_evaluation_run(evaluation_run), 200
-        except EvaluationFrameworkNotConfiguredError as e:
-            return {"message": str(e.description)}, 400
-        except EvaluationNotFoundError as e:
-            return {"message": str(e.description)}, 404
-        except EvaluationMaxConcurrentRunsError as e:
-            return {"message": str(e.description)}, 429
-        except EvaluationDatasetInvalidError as e:
-            return {"message": str(e.description)}, 400
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation/logs")
-class DatasetEvaluationLogsApi(Resource):
-    @console_ns.doc("get_dataset_evaluation_logs")
-    @console_ns.response(200, "Evaluation logs retrieved")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self, dataset_id):
-        """Get evaluation run history for the knowledge base."""
-        current_user, current_tenant_id = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        page = request.args.get("page", 1, type=int)
-        page_size = request.args.get("page_size", 20, type=int)
-
-        with Session(db.engine, expire_on_commit=False) as session:
-            runs, total = EvaluationService.get_evaluation_runs(
-                session=session,
-                tenant_id=current_tenant_id,
-                target_type="dataset",
-                target_id=dataset_id_str,
-                page=page,
-                page_size=page_size,
-            )
-
-        return {
-            "data": [_serialize_dataset_evaluation_run(run) for run in runs],
-            "total": total,
-            "page": page,
-            "page_size": page_size,
-        }
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation/runs/<uuid:run_id>")
-class DatasetEvaluationRunDetailApi(Resource):
-    @console_ns.doc("get_dataset_evaluation_run_detail")
-    @console_ns.response(200, "Evaluation run detail retrieved")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset or run not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self, dataset_id, run_id):
-        """Get evaluation run detail including per-item results."""
-        current_user, current_tenant_id = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        run_id_str = str(run_id)
-        page = request.args.get("page", 1, type=int)
-        page_size = request.args.get("page_size", 50, type=int)
-
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                run = EvaluationService.get_evaluation_run_detail(
-                    session=session,
-                    tenant_id=current_tenant_id,
-                    run_id=run_id_str,
-                )
-                items, total_items = EvaluationService.get_evaluation_run_items(
-                    session=session,
-                    run_id=run_id_str,
-                    page=page,
-                    page_size=page_size,
-                )
-                return {
-                    "run": _serialize_dataset_evaluation_run(run),
-                    "items": {
-                        "data": [_serialize_dataset_evaluation_run_item(item) for item in items],
-                        "total": total_items,
-                        "page": page,
-                        "page_size": page_size,
-                    },
-                }
-        except EvaluationNotFoundError as e:
-            return {"message": str(e.description)}, 404
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation/runs/<uuid:run_id>/cancel")
-class DatasetEvaluationRunCancelApi(Resource):
-    @console_ns.doc("cancel_dataset_evaluation_run")
-    @console_ns.response(200, "Evaluation run cancelled")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset or run not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def post(self, dataset_id, run_id):
-        """Cancel a running knowledge base evaluation."""
-        current_user, current_tenant_id = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        run_id_str = str(run_id)
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                run = EvaluationService.cancel_evaluation_run(
-                    session=session,
-                    tenant_id=current_tenant_id,
-                    run_id=run_id_str,
-                )
-                return _serialize_dataset_evaluation_run(run)
-        except EvaluationNotFoundError as e:
-            return {"message": str(e.description)}, 404
-        except ValueError as e:
-            return {"message": str(e)}, 400
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation/metrics")
-class DatasetEvaluationMetricsApi(Resource):
-    @console_ns.doc("get_dataset_evaluation_metrics")
-    @console_ns.response(200, "Available retrieval metrics retrieved")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self, dataset_id):
-        """Get available evaluation metrics for knowledge base retrieval."""
-        current_user, _ = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        return {
-            "metrics": EvaluationService.get_supported_metrics(EvaluationCategory.RETRIEVAL)
-        }
-
-
-@console_ns.route("/datasets/<uuid:dataset_id>/evaluation/files/<uuid:file_id>")
-class DatasetEvaluationFileDownloadApi(Resource):
-    @console_ns.doc("download_dataset_evaluation_file")
-    @console_ns.response(200, "File download URL generated")
-    @console_ns.response(403, "Permission denied")
-    @console_ns.response(404, "Dataset or file not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self, dataset_id, file_id):
-        """Download evaluation test file or result file for the knowledge base."""
-        from core.workflow.file import helpers as file_helpers
-
-        current_user, current_tenant_id = current_account_with_tenant()
-        dataset_id_str = str(dataset_id)
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        file_id_str = str(file_id)
-        with Session(db.engine, expire_on_commit=False) as session:
-            stmt = select(UploadFile).where(
-                UploadFile.id == file_id_str,
-                UploadFile.tenant_id == current_tenant_id,
-            )
-            upload_file = session.execute(stmt).scalar_one_or_none()
-
-        if not upload_file:
-            raise NotFound("File not found.")
-
-        download_url = file_helpers.get_signed_file_url(upload_file_id=upload_file.id, as_attachment=True)
-
-        return {
-            "id": upload_file.id,
-            "name": upload_file.name,
-            "size": upload_file.size,
-            "extension": upload_file.extension,
-            "mime_type": upload_file.mime_type,
-            "created_at": int(upload_file.created_at.timestamp()) if upload_file.created_at else None,
-            "download_url": download_url,
-        }

api/controllers/console/datasets/datasets_document.py

@@ -3,18 +3,19 @@ import logging
 from argparse import ArgumentTypeError
 from collections.abc import Sequence
 from contextlib import ExitStack
+from datetime import datetime
 from typing import Any, Literal, cast
 
 import sqlalchemy as sa
 from flask import request, send_file
-from flask_restx import Resource, fields, marshal, marshal_with
-from pydantic import BaseModel, Field
+from flask_restx import Resource, marshal
+from pydantic import BaseModel, Field, field_validator
 from sqlalchemy import asc, desc, func, select
 from werkzeug.exceptions import Forbidden, NotFound
 
 import services
 from controllers.common.controller_schemas import DocumentBatchDownloadZipPayload
-from controllers.common.schema import get_or_create_model, register_schema_models
+from controllers.common.schema import register_schema_models
 from controllers.console import console_ns
 from core.errors.error import (
     LLMBadRequestError,
@@ -29,17 +30,16 @@ from core.rag.extractor.entity.datasource_type import DatasourceType
 from core.rag.extractor.entity.extract_setting import ExtractSetting, NotionInfo, WebsiteInfo
 from core.rag.index_processor.constant.index_type import IndexTechniqueType
 from extensions.ext_database import db
-from fields.dataset_fields import dataset_fields
+from fields.base import ResponseModel
 from fields.document_fields import (
-    dataset_and_document_fields,
     document_fields,
-    document_metadata_fields,
     document_status_fields,
     document_with_segments_fields,
 )
 from graphon.model_runtime.entities.model_entities import ModelType
 from graphon.model_runtime.errors.invoke import InvokeAuthorizationError
 from libs.datetime_utils import naive_utc_now
+from libs.helper import to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models import DatasetProcessRule, Document, DocumentSegment, UploadFile
 from models.dataset import DocumentPipelineExecutionLog
@@ -72,27 +72,94 @@ from ..wraps import (
 logger = logging.getLogger(__name__)
 
 
-# Register models for flask_restx to avoid dict type issues in Swagger
-dataset_model = get_or_create_model("Dataset", dataset_fields)
+def _normalize_enum(value: Any) -> Any:
+    if isinstance(value, str) or value is None:
+        return value
+    return getattr(value, "value", value)
 
-document_metadata_model = get_or_create_model("DocumentMetadata", document_metadata_fields)
 
-document_fields_copy = document_fields.copy()
-document_fields_copy["doc_metadata"] = fields.List(
-    fields.Nested(document_metadata_model), attribute="doc_metadata_details"
-)
-document_model = get_or_create_model("Document", document_fields_copy)
+class DatasetResponse(ResponseModel):
+    id: str
+    name: str
+    description: str | None = None
+    permission: str | None = None
+    data_source_type: str | None = None
+    indexing_technique: str | None = None
+    created_by: str | None = None
+    created_at: int | None = None
 
-document_with_segments_fields_copy = document_with_segments_fields.copy()
-document_with_segments_fields_copy["doc_metadata"] = fields.List(
-    fields.Nested(document_metadata_model), attribute="doc_metadata_details"
-)
-document_with_segments_model = get_or_create_model("DocumentWithSegments", document_with_segments_fields_copy)
+    @field_validator("data_source_type", "indexing_technique", mode="before")
+    @classmethod
+    def _normalize_enum_fields(cls, value: Any) -> Any:
+        return _normalize_enum(value)
 
-dataset_and_document_fields_copy = dataset_and_document_fields.copy()
-dataset_and_document_fields_copy["dataset"] = fields.Nested(dataset_model)
-dataset_and_document_fields_copy["documents"] = fields.List(fields.Nested(document_model))
-dataset_and_document_model = get_or_create_model("DatasetAndDocument", dataset_and_document_fields_copy)
+    @field_validator("created_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class DocumentMetadataResponse(ResponseModel):
+    id: str
+    name: str
+    type: str
+    value: str | None = None
+
+
+class DocumentResponse(ResponseModel):
+    id: str
+    position: int | None = None
+    data_source_type: str | None = None
+    data_source_info: Any = Field(default=None, validation_alias="data_source_info_dict")
+    data_source_detail_dict: Any = None
+    dataset_process_rule_id: str | None = None
+    name: str
+    created_from: str | None = None
+    created_by: str | None = None
+    created_at: int | None = None
+    tokens: int | None = None
+    indexing_status: str | None = None
+    error: str | None = None
+    enabled: bool | None = None
+    disabled_at: int | None = None
+    disabled_by: str | None = None
+    archived: bool | None = None
+    display_status: str | None = None
+    word_count: int | None = None
+    hit_count: int | None = None
+    doc_form: str | None = None
+    doc_metadata: list[DocumentMetadataResponse] = Field(default_factory=list, validation_alias="doc_metadata_details")
+    summary_index_status: str | None = None
+    need_summary: bool | None = None
+
+    @field_validator("data_source_type", "indexing_status", "display_status", "doc_form", mode="before")
+    @classmethod
+    def _normalize_enum_fields(cls, value: Any) -> Any:
+        return _normalize_enum(value)
+
+    @field_validator("doc_metadata", mode="before")
+    @classmethod
+    def _normalize_doc_metadata(cls, value: Any) -> list[Any]:
+        if value is None:
+            return []
+        return value
+
+    @field_validator("created_at", "disabled_at", mode="before")
+    @classmethod
+    def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
+        return to_timestamp(value)
+
+
+class DocumentWithSegmentsResponse(DocumentResponse):
+    process_rule_dict: Any = None
+    completed_segments: int | None = None
+    total_segments: int | None = None
+
+
+class DatasetAndDocumentResponse(ResponseModel):
+    dataset: DatasetResponse
+    documents: list[DocumentResponse]
+    batch: str
 
 
 class DocumentRetryPayload(BaseModel):
@@ -107,6 +174,11 @@ class GenerateSummaryPayload(BaseModel):
     document_list: list[str]
 
 
+class DocumentMetadataUpdatePayload(BaseModel):
+    doc_type: str | None = None
+    doc_metadata: Any = None
+
+
 class DocumentDatasetListParam(BaseModel):
     page: int = Field(1, title="Page", description="Page number.")
     limit: int = Field(20, title="Limit", description="Page size.")
@@ -124,7 +196,13 @@ register_schema_models(
     DocumentRetryPayload,
     DocumentRenamePayload,
     GenerateSummaryPayload,
+    DocumentMetadataUpdatePayload,
     DocumentBatchDownloadZipPayload,
+    DatasetResponse,
+    DocumentMetadataResponse,
+    DocumentResponse,
+    DocumentWithSegmentsResponse,
+    DatasetAndDocumentResponse,
 )
 
 
@@ -360,10 +438,10 @@ class DatasetDocumentListApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @marshal_with(dataset_and_document_model)
     @cloud_edition_billing_resource_check("vector_space")
     @cloud_edition_billing_rate_limit_check("knowledge")
     @console_ns.expect(console_ns.models[KnowledgeConfig.__name__])
+    @console_ns.response(200, "Documents created successfully", console_ns.models[DatasetAndDocumentResponse.__name__])
     def post(self, dataset_id):
         current_user, _ = current_account_with_tenant()
         dataset_id = str(dataset_id)
@@ -401,7 +479,9 @@ class DatasetDocumentListApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
 
-        return {"dataset": dataset, "documents": documents, "batch": batch}
+        return DatasetAndDocumentResponse.model_validate(
+            {"dataset": dataset, "documents": documents, "batch": batch}, from_attributes=True
+        ).model_dump(mode="json")
 
     @setup_required
     @login_required
@@ -429,12 +509,13 @@ class DatasetInitApi(Resource):
     @console_ns.doc("init_dataset")
     @console_ns.doc(description="Initialize dataset with documents")
     @console_ns.expect(console_ns.models[KnowledgeConfig.__name__])
-    @console_ns.response(201, "Dataset initialized successfully", dataset_and_document_model)
+    @console_ns.response(
+        201, "Dataset initialized successfully", console_ns.models[DatasetAndDocumentResponse.__name__]
+    )
     @console_ns.response(400, "Invalid request parameters")
     @setup_required
     @login_required
     @account_initialization_required
-    @marshal_with(dataset_and_document_model)
     @cloud_edition_billing_resource_check("vector_space")
     @cloud_edition_billing_rate_limit_check("knowledge")
     def post(self):
@@ -482,9 +563,9 @@ class DatasetInitApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
 
-        response = {"dataset": dataset, "documents": documents, "batch": batch}
-
-        return response
+        return DatasetAndDocumentResponse.model_validate(
+            {"dataset": dataset, "documents": documents, "batch": batch}, from_attributes=True
+        ).model_dump(mode="json")
 
 
 @console_ns.route("/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/indexing-estimate")
@@ -991,15 +1072,7 @@ class DocumentMetadataApi(DocumentResource):
     @console_ns.doc("update_document_metadata")
     @console_ns.doc(description="Update document metadata")
     @console_ns.doc(params={"dataset_id": "Dataset ID", "document_id": "Document ID"})
-    @console_ns.expect(
-        console_ns.model(
-            "UpdateDocumentMetadataRequest",
-            {
-                "doc_type": fields.String(description="Document type"),
-                "doc_metadata": fields.Raw(description="Document metadata"),
-            },
-        )
-    )
+    @console_ns.expect(console_ns.models[DocumentMetadataUpdatePayload.__name__])
     @console_ns.response(200, "Document metadata updated successfully")
     @console_ns.response(404, "Document not found")
     @console_ns.response(403, "Permission denied")
@@ -1012,10 +1085,10 @@ class DocumentMetadataApi(DocumentResource):
         document_id = str(document_id)
         document = self.get_document(dataset_id, document_id)
 
-        req_data = request.get_json()
+        req_data = DocumentMetadataUpdatePayload.model_validate(request.get_json() or {})
 
-        doc_type = req_data.get("doc_type")
-        doc_metadata = req_data.get("doc_metadata")
+        doc_type = req_data.doc_type
+        doc_metadata = req_data.doc_metadata
 
         # The role of the current user in the ta table must be admin, owner, dataset_operator, or editor
         if not current_user.is_dataset_editor:
@@ -1197,7 +1270,7 @@ class DocumentRenameApi(DocumentResource):
     @setup_required
     @login_required
     @account_initialization_required
-    @marshal_with(document_model)
+    @console_ns.response(200, "Document renamed successfully", console_ns.models[DocumentResponse.__name__])
     @console_ns.expect(console_ns.models[DocumentRenamePayload.__name__])
     def post(self, dataset_id, document_id):
         # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
@@ -1215,7 +1288,7 @@ class DocumentRenameApi(DocumentResource):
         except services.errors.document.DocumentIndexingError:
             raise DocumentIndexingError("Cannot delete document during indexing.")
 
-        return document
+        return DocumentResponse.model_validate(document, from_attributes=True).model_dump(mode="json")
 
 
 @console_ns.route("/datasets/<uuid:dataset_id>/documents/<uuid:document_id>/website-sync")

api/controllers/console/datasets/hit_testing.py

@@ -8,6 +8,7 @@ from pydantic import Field, field_validator
 
 from controllers.common.schema import register_schema_models
 from fields.base import ResponseModel
+from libs.helper import to_timestamp
 from libs.login import login_required
 
 from .. import console_ns
@@ -19,12 +20,6 @@ from ..wraps import (
 )
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 class HitTestingDocument(ResponseModel):
     id: str | None = None
     data_source_type: str | None = None
@@ -61,7 +56,7 @@ class HitTestingSegment(ResponseModel):
     @field_validator("disabled_at", "created_at", "indexing_at", "completed_at", "stopped_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class HitTestingChildChunk(ResponseModel):

api/controllers/console/datasets/hit_testing_base.py

@@ -39,11 +39,8 @@ class HitTestingPayload(BaseModel):
 
 class DatasetsHitTestingBase:
     @staticmethod
-    def _normalize_hit_testing_query(query: Any) -> str:
-        """Return the user-visible query string from legacy and current response shapes."""
-        if isinstance(query, str):
-            return query
-
+    def _extract_hit_testing_query(query: Any) -> str:
+        """Return the query string from the service response shape."""
         if isinstance(query, dict):
             content = query.get("content")
             if isinstance(content, str):
@@ -52,15 +49,15 @@ class DatasetsHitTestingBase:
         raise ValueError("Invalid hit testing query response")
 
     @staticmethod
-    def _normalize_hit_testing_records(records: Any) -> list[dict[str, Any]]:
-        """Coerce nullable collection fields into lists before response validation."""
+    def _prepare_hit_testing_records(records: Any) -> list[dict[str, Any]]:
+        """Ensure collection fields match the API schema before response validation."""
         if not isinstance(records, list):
-            return []
+            raise ValueError("Invalid hit testing records response")
 
         normalized_records: list[dict[str, Any]] = []
         for record in records:
             if not isinstance(record, dict):
-                continue
+                raise ValueError("Invalid hit testing record response")
 
             normalized_record = dict(record)
             segment = normalized_record.get("segment")
@@ -118,8 +115,8 @@ class DatasetsHitTestingBase:
                 limit=10,
             )
             return {
-                "query": DatasetsHitTestingBase._normalize_hit_testing_query(response.get("query")),
-                "records": DatasetsHitTestingBase._normalize_hit_testing_records(
+                "query": DatasetsHitTestingBase._extract_hit_testing_query(response.get("query")),
+                "records": DatasetsHitTestingBase._prepare_hit_testing_records(
                     marshal(response.get("records", []), hit_testing_record_fields)
                 ),
             }

api/controllers/console/evaluation/__init__.py

@@ -1 +0,0 @@
-# Evaluation controller module

api/controllers/console/evaluation/evaluation.py

@@ -1,993 +0,0 @@
-from __future__ import annotations
-
-import logging
-from collections.abc import Callable
-from functools import wraps
-from typing import TYPE_CHECKING, Union
-from urllib.parse import quote
-
-from flask import Response, request
-from flask_restx import Resource, fields, marshal
-from pydantic import BaseModel
-from sqlalchemy import select
-from sqlalchemy.orm import Session
-from werkzeug.exceptions import BadRequest, Forbidden, NotFound
-
-from controllers.common.schema import register_schema_models
-from controllers.console import console_ns
-from controllers.console.app.workflow import WorkflowListQuery
-from controllers.console.wraps import (
-    account_initialization_required,
-    edit_permission_required,
-    setup_required,
-)
-from core.evaluation.entities.evaluation_entity import EvaluationCategory, EvaluationConfigData, EvaluationRunRequest
-from extensions.ext_database import db
-from extensions.ext_storage import storage
-from fields.member_fields import simple_account_fields
-from graphon.file import helpers as file_helpers
-from libs.helper import TimestampField
-from libs.login import current_account_with_tenant, login_required
-from models import App, Dataset
-from models.evaluation import EvaluationTargetType
-from models.model import UploadFile
-from models.snippet import CustomizedSnippet
-from services.errors.evaluation import (
-    EvaluationDatasetInvalidError,
-    EvaluationFrameworkNotConfiguredError,
-    EvaluationMaxConcurrentRunsError,
-    EvaluationNotFoundError,
-)
-from services.evaluation_service import EvaluationService
-from services.workflow_service import WorkflowService
-
-if TYPE_CHECKING:
-    from models.evaluation import EvaluationRun, EvaluationRunItem
-
-logger = logging.getLogger(__name__)
-
-EVALUATE_TARGET_TYPES = {
-    EvaluationTargetType.APPS.value,
-    EvaluationTargetType.SNIPPETS.value,
-}
-
-
-class VersionQuery(BaseModel):
-    """Query parameters for version endpoint."""
-
-    version: str
-
-
-register_schema_models(
-    console_ns,
-    VersionQuery,
-)
-
-
-# Response field definitions
-file_info_fields = {
-    "id": fields.String,
-    "name": fields.String,
-}
-
-evaluation_log_fields = {
-    "created_at": TimestampField,
-    "created_by": fields.String,
-    "test_file": fields.Nested(
-        console_ns.model(
-            "EvaluationTestFile",
-            file_info_fields,
-        )
-    ),
-    "result_file": fields.Nested(
-        console_ns.model(
-            "EvaluationResultFile",
-            file_info_fields,
-        ),
-        allow_null=True,
-    ),
-    "version": fields.String,
-}
-
-evaluation_log_list_model = console_ns.model(
-    "EvaluationLogList",
-    {
-        "data": fields.List(fields.Nested(console_ns.model("EvaluationLog", evaluation_log_fields))),
-    },
-)
-
-evaluation_default_metric_node_info_fields = {
-    "node_id": fields.String,
-    "type": fields.String,
-    "title": fields.String,
-}
-evaluation_default_metric_item_fields = {
-    "metric": fields.String,
-    "value_type": fields.String,
-    "node_info_list": fields.List(
-        fields.Nested(
-            console_ns.model("EvaluationDefaultMetricNodeInfo", evaluation_default_metric_node_info_fields),
-        ),
-    ),
-}
-
-customized_metrics_fields = {
-    "evaluation_workflow_id": fields.String,
-    "input_fields": fields.Raw,
-    "output_fields": fields.Raw,
-}
-
-judgment_condition_fields = {
-    "variable_selector": fields.List(fields.String),
-    "comparison_operator": fields.String,
-    "value": fields.String,
-}
-
-judgment_config_fields = {
-    "logical_operator": fields.String,
-    "conditions": fields.List(fields.Nested(console_ns.model("JudgmentCondition", judgment_condition_fields))),
-}
-
-evaluation_detail_fields = {
-    "evaluation_model": fields.String,
-    "evaluation_model_provider": fields.String,
-    "default_metrics": fields.List(
-        fields.Nested(console_ns.model("EvaluationDefaultMetricItem_Detail", evaluation_default_metric_item_fields)),
-        allow_null=True,
-    ),
-    "customized_metrics": fields.Nested(
-        console_ns.model("EvaluationCustomizedMetrics", customized_metrics_fields),
-        allow_null=True,
-    ),
-    "judgment_config": fields.Nested(
-        console_ns.model("EvaluationJudgmentConfig", judgment_config_fields),
-        allow_null=True,
-    ),
-}
-
-evaluation_detail_model = console_ns.model("EvaluationDetail", evaluation_detail_fields)
-
-available_evaluation_workflow_list_fields = {
-    "id": fields.String,
-    "app_id": fields.String,
-    "app_name": fields.String,
-    "type": fields.String,
-    "kind": fields.String,
-    "version": fields.String,
-    "marked_name": fields.String,
-    "marked_comment": fields.String,
-    "hash": fields.String,
-    "created_by": fields.Nested(simple_account_fields),
-    "created_at": TimestampField,
-    "updated_by": fields.Nested(simple_account_fields, allow_null=True),
-    "updated_at": TimestampField,
-}
-
-available_evaluation_workflow_pagination_fields = {
-    "items": fields.List(fields.Nested(available_evaluation_workflow_list_fields)),
-    "page": fields.Integer,
-    "limit": fields.Integer,
-    "has_more": fields.Boolean,
-}
-
-available_evaluation_workflow_pagination_model = console_ns.model(
-    "AvailableEvaluationWorkflowPagination",
-    available_evaluation_workflow_pagination_fields,
-)
-
-evaluation_default_metrics_response_model = console_ns.model(
-    "EvaluationDefaultMetricsResponse",
-    {
-        "default_metrics": fields.List(
-            fields.Nested(console_ns.model("EvaluationDefaultMetricItem", evaluation_default_metric_item_fields)),
-        ),
-    },
-)
-
-evaluation_dataset_columns_response_model = console_ns.model(
-    "EvaluationDatasetColumnsResponse",
-    {
-        "columns": fields.List(
-            fields.Nested(
-                console_ns.model(
-                    "EvaluationTemplateColumn",
-                    {
-                        "name": fields.String,
-                        "type": fields.String,
-                    },
-                )
-            )
-        ),
-    },
-)
-
-
-def get_evaluation_target[**P, R](view_func: Callable[P, R]) -> Callable[P, R]:
-    """
-    Decorator to resolve polymorphic evaluation target (apps or snippets).
-
-    Validates the target_type parameter and fetches the corresponding
-    model (App or CustomizedSnippet) with tenant isolation.
-    """
-
-    @wraps(view_func)
-    def decorated_view(*args: P.args, **kwargs: P.kwargs) -> R:
-        target_type = kwargs.get("evaluate_target_type")
-        target_id = kwargs.get("evaluate_target_id")
-
-        if target_type not in EVALUATE_TARGET_TYPES:
-            raise NotFound(f"Invalid evaluation target type: {target_type}")
-
-        _, current_tenant_id = current_account_with_tenant()
-
-        target_id = str(target_id)
-
-        # Remove path parameters
-        del kwargs["evaluate_target_type"]
-        del kwargs["evaluate_target_id"]
-
-        target: Union[App, CustomizedSnippet] | None = None
-
-        if target_type == EvaluationTargetType.APPS.value:
-            target = db.session.query(App).where(App.id == target_id, App.tenant_id == current_tenant_id).first()
-        elif target_type == EvaluationTargetType.SNIPPETS.value:
-            target = (
-                db.session.query(CustomizedSnippet)
-                .where(CustomizedSnippet.id == target_id, CustomizedSnippet.tenant_id == current_tenant_id)
-                .first()
-            )
-
-        if not target:
-            raise NotFound(f"{str(target_type)} not found")
-
-        kwargs["target"] = target
-        kwargs["target_type"] = target_type
-
-        return view_func(*args, **kwargs)
-
-    return decorated_view
-
-
-def _load_evaluation_run_request_and_dataset(tenant_id: str) -> tuple[EvaluationRunRequest, bytes, str]:
-    """Validate the run payload and load the uploaded dataset bytes."""
-    body = request.get_json(force=True)
-    if not body:
-        raise BadRequest("Request body is required.")
-
-    try:
-        run_request = EvaluationRunRequest.model_validate(body)
-    except Exception as e:
-        raise BadRequest(f"Invalid request body: {e}")
-
-    upload_file = db.session.query(UploadFile).filter_by(id=run_request.file_id, tenant_id=tenant_id).first()
-    if not upload_file:
-        raise NotFound("Dataset file not found.")
-
-    try:
-        dataset_content = storage.load_once(upload_file.key)
-    except Exception:
-        raise BadRequest("Failed to read dataset file.")
-
-    if not dataset_content:
-        raise BadRequest("Dataset file is empty.")
-
-    return run_request, dataset_content, upload_file.name
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/dataset-template/download")
-class EvaluationDatasetTemplateDownloadApi(Resource):
-    @console_ns.doc("download_evaluation_dataset_template")
-    @console_ns.response(200, "Template file streamed as XLSX attachment")
-    @console_ns.response(400, "Invalid target type or excluded app mode")
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    @edit_permission_required
-    def post(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """
-        Download evaluation dataset template.
-
-        Generates an XLSX template based on the target's input parameters
-        and streams it directly as a file attachment.
-        """
-        try:
-            xlsx_content, filename = EvaluationService.generate_dataset_template(
-                target=target,
-                target_type=target_type,
-            )
-        except ValueError as e:
-            return {"message": str(e)}, 400
-
-        encoded_filename = quote(filename)
-        response = Response(
-            xlsx_content,
-            mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
-        )
-        response.headers["Content-Disposition"] = f"attachment; filename*=UTF-8''{encoded_filename}"
-        response.headers["Content-Length"] = str(len(xlsx_content))
-        return response
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation")
-class EvaluationDetailApi(Resource):
-    @console_ns.doc("get_evaluation_detail")
-    @console_ns.response(200, "Evaluation details retrieved successfully", evaluation_detail_model)
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def get(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """
-        Get evaluation configuration for the target.
-
-        Returns evaluation configuration including model settings,
-        metrics config, and judgement conditions.
-        """
-        _, current_tenant_id = current_account_with_tenant()
-
-        with Session(db.engine, expire_on_commit=False) as session:
-            config = EvaluationService.get_evaluation_config(session, current_tenant_id, target_type, str(target.id))
-
-        if config is None:
-            return {
-                "evaluation_model": None,
-                "evaluation_model_provider": None,
-                "default_metrics": None,
-                "customized_metrics": None,
-                "judgment_config": None,
-            }
-
-        return {
-            "evaluation_model": config.evaluation_model,
-            "evaluation_model_provider": config.evaluation_model_provider,
-            "default_metrics": EvaluationService.serialize_console_default_metrics(config.default_metrics_list),
-            "customized_metrics": config.customized_metrics_dict,
-            "judgment_config": EvaluationService.serialize_console_judgment_config(config.judgment_config_dict),
-        }
-
-    @console_ns.doc("save_evaluation_detail")
-    @console_ns.response(200, "Evaluation configuration saved successfully")
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    @edit_permission_required
-    def put(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """
-        Save evaluation configuration for the target.
-        """
-        current_account, current_tenant_id = current_account_with_tenant()
-        body = request.get_json(force=True)
-
-        try:
-            config_data = EvaluationConfigData.model_validate(body)
-        except Exception as e:
-            raise BadRequest(f"Invalid request body: {e}")
-
-        with Session(db.engine, expire_on_commit=False) as session:
-            config = EvaluationService.save_evaluation_config(
-                session=session,
-                tenant_id=current_tenant_id,
-                target_type=target_type,
-                target_id=str(target.id),
-                account_id=str(current_account.id),
-                data=config_data,
-            )
-
-        return {
-            "evaluation_model": config.evaluation_model,
-            "evaluation_model_provider": config.evaluation_model_provider,
-            "default_metrics": EvaluationService.serialize_console_default_metrics(config.default_metrics_list),
-            "customized_metrics": config.customized_metrics_dict,
-            "judgment_config": EvaluationService.serialize_console_judgment_config(config.judgment_config_dict),
-        }
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/template-columns")
-class EvaluationTemplateColumnsApi(Resource):
-    @console_ns.doc("get_evaluation_template_columns")
-    @console_ns.response(200, "Evaluation dataset columns resolved", evaluation_dataset_columns_response_model)
-    @console_ns.response(400, "Invalid request body")
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def post(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """Return the dataset template columns implied by the current evaluation config."""
-        body = request.get_json(silent=True) or {}
-        try:
-            config_data = EvaluationConfigData.model_validate(body)
-        except Exception as e:
-            raise BadRequest(f"Invalid request body: {e}")
-
-        return {
-            "columns": EvaluationService.get_dataset_column_names(
-                target=target,
-                target_type=target_type,
-                data=config_data,
-            )
-        }
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/logs")
-class EvaluationLogsApi(Resource):
-    @console_ns.doc("get_evaluation_logs")
-    @console_ns.response(200, "Evaluation logs retrieved successfully")
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def get(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """
-        Get evaluation run history for the target.
-
-        Returns a paginated list of evaluation runs.
-        """
-        _, current_tenant_id = current_account_with_tenant()
-        page = request.args.get("page", 1, type=int)
-        page_size = request.args.get("page_size", 20, type=int)
-
-        with Session(db.engine, expire_on_commit=False) as session:
-            runs, total = EvaluationService.get_evaluation_runs(
-                session=session,
-                tenant_id=current_tenant_id,
-                target_type=target_type,
-                target_id=str(target.id),
-                page=page,
-                page_size=page_size,
-            )
-
-        return {
-            "data": [_serialize_evaluation_run(run) for run in runs],
-            "total": total,
-            "page": page,
-            "page_size": page_size,
-        }
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/run1")
-class EvaluationRunApi(Resource):
-    @console_ns.doc("start_evaluation_run")
-    @console_ns.response(200, "Evaluation run started")
-    @console_ns.response(400, "Invalid request")
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    @edit_permission_required
-    def post(self, target: Union[App, CustomizedSnippet, Dataset], target_type: str):
-        """
-        Start an evaluation run.
-
-        Expects JSON body with:
-        - file_id: uploaded dataset file ID
-        - evaluation_model: evaluation model name
-        - evaluation_model_provider: evaluation model provider
-        - default_metrics: list of default metric objects
-        - customized_metrics: customized metrics object (optional)
-        - judgment_config: judgment conditions config (optional)
-        """
-        current_account, current_tenant_id = current_account_with_tenant()
-        run_request, dataset_content, dataset_filename = _load_evaluation_run_request_and_dataset(current_tenant_id)
-
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                if target_type == EvaluationTargetType.APPS.value:
-                    evaluation_run = EvaluationService.start_stub_evaluation_run(
-                        session=session,
-                        tenant_id=current_tenant_id,
-                        target_type=target_type,
-                        target_id=str(target.id),
-                        account_id=str(current_account.id),
-                        dataset_file_content=dataset_content,
-                        dataset_filename=dataset_filename,
-                        run_request=run_request,
-                    )
-                else:
-                    evaluation_run = EvaluationService.start_evaluation_run(
-                        session=session,
-                        tenant_id=current_tenant_id,
-                        target_type=target_type,
-                        target_id=str(target.id),
-                        account_id=str(current_account.id),
-                        dataset_file_content=dataset_content,
-                        dataset_filename=dataset_filename,
-                        run_request=run_request,
-                    )
-                return _serialize_evaluation_run(evaluation_run), 200
-        except EvaluationFrameworkNotConfiguredError as e:
-            return {"message": str(e.description)}, 400
-        except EvaluationNotFoundError as e:
-            return {"message": str(e.description)}, 404
-        except EvaluationMaxConcurrentRunsError as e:
-            return {"message": str(e.description)}, 429
-        except EvaluationDatasetInvalidError as e:
-            return {"message": str(e.description)}, 400
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/run")
-class EvaluationRunRealApi(Resource):
-    @console_ns.doc("start_evaluation_run_real")
-    @console_ns.response(200, "Evaluation run started")
-    @console_ns.response(400, "Invalid request")
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    @edit_permission_required
-    def post(self, target: Union[App, CustomizedSnippet, Dataset], target_type: str):
-        """Start the real evaluation execution flow on the temporary dev path."""
-        current_account, current_tenant_id = current_account_with_tenant()
-        run_request, dataset_content, dataset_filename = _load_evaluation_run_request_and_dataset(current_tenant_id)
-
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                evaluation_run = EvaluationService.start_evaluation_run(
-                    session=session,
-                    tenant_id=current_tenant_id,
-                    target_type=target_type,
-                    target_id=str(target.id),
-                    account_id=str(current_account.id),
-                    dataset_file_content=dataset_content,
-                    dataset_filename=dataset_filename,
-                    run_request=run_request,
-                )
-                return _serialize_evaluation_run(evaluation_run), 200
-        except EvaluationFrameworkNotConfiguredError as e:
-            return {"message": str(e.description)}, 400
-        except EvaluationNotFoundError as e:
-            return {"message": str(e.description)}, 404
-        except EvaluationMaxConcurrentRunsError as e:
-            return {"message": str(e.description)}, 429
-        except EvaluationDatasetInvalidError as e:
-            return {"message": str(e.description)}, 400
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/runs/<uuid:run_id>")
-class EvaluationRunDetailApi(Resource):
-    @console_ns.doc("get_evaluation_run_detail")
-    @console_ns.response(200, "Evaluation run detail retrieved")
-    @console_ns.response(404, "Run not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def get(self, target: Union[App, CustomizedSnippet], target_type: str, run_id: str):
-        """
-        Get evaluation run detail including items.
-        """
-        _, current_tenant_id = current_account_with_tenant()
-        run_id = str(run_id)
-        page = request.args.get("page", 1, type=int)
-        page_size = request.args.get("page_size", 50, type=int)
-
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                run = EvaluationService.get_evaluation_run_detail(
-                    session=session,
-                    tenant_id=current_tenant_id,
-                    run_id=run_id,
-                )
-                items, total_items = EvaluationService.get_evaluation_run_items(
-                    session=session,
-                    run_id=run_id,
-                    page=page,
-                    page_size=page_size,
-                )
-
-                return {
-                    "run": _serialize_evaluation_run(run),
-                    "items": {
-                        "data": [_serialize_evaluation_run_item(item) for item in items],
-                        "total": total_items,
-                        "page": page,
-                        "page_size": page_size,
-                    },
-                }
-        except EvaluationNotFoundError as e:
-            return {"message": str(e.description)}, 404
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/runs/<uuid:run_id>/cancel")
-class EvaluationRunCancelApi(Resource):
-    @console_ns.doc("cancel_evaluation_run")
-    @console_ns.response(200, "Evaluation run cancelled")
-    @console_ns.response(404, "Run not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    @edit_permission_required
-    def post(self, target: Union[App, CustomizedSnippet], target_type: str, run_id: str):
-        """Cancel a running evaluation."""
-        _, current_tenant_id = current_account_with_tenant()
-        run_id = str(run_id)
-
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                run = EvaluationService.cancel_evaluation_run(
-                    session=session,
-                    tenant_id=current_tenant_id,
-                    run_id=run_id,
-                )
-                return _serialize_evaluation_run(run)
-        except EvaluationNotFoundError as e:
-            return {"message": str(e.description)}, 404
-        except ValueError as e:
-            return {"message": str(e)}, 400
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/metrics")
-class EvaluationMetricsApi(Resource):
-    @console_ns.doc("get_evaluation_metrics")
-    @console_ns.response(200, "Available metrics retrieved")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def get(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """
-        Get available evaluation metrics for the current framework.
-        """
-        result = {}
-        for category in EvaluationCategory:
-            if category in EvaluationService.CONSOLE_DISABLED_CATEGORIES:
-                continue
-            result[category.value] = EvaluationService.get_supported_metrics(category)
-        return {"metrics": result}
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/default-metrics")
-class EvaluationDefaultMetricsApi(Resource):
-    @console_ns.doc(
-        "get_evaluation_default_metrics_with_nodes",
-        description=(
-            "List default metrics supported by the current evaluation framework with matching nodes "
-            "from the target's published workflow only (draft is ignored)."
-        ),
-    )
-    @console_ns.response(
-        200,
-        "Default metrics and node candidates for the published workflow",
-        evaluation_default_metrics_response_model,
-    )
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def get(self, target: Union[App, CustomizedSnippet], target_type: str):
-        default_metrics = EvaluationService.get_default_metrics_with_nodes_for_published_target(
-            target=target,
-            target_type=target_type,
-        )
-        return {
-            "default_metrics": [
-                m.model_dump() for m in EvaluationService.filter_console_default_metrics(default_metrics)
-            ]
-        }
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/node-info")
-class EvaluationNodeInfoApi(Resource):
-    @console_ns.doc("get_evaluation_node_info")
-    @console_ns.response(200, "Node info grouped by metric")
-    @console_ns.response(404, "Target not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def post(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """Return workflow/snippet node info grouped by requested metrics.
-
-        Request body (JSON):
-            - metrics: list[str] | None  – metric names to query; omit or pass
-              an empty list to get all nodes under key ``"all"``.
-
-        Response:
-            ``{metric_or_all: [{"node_id": ..., "type": ..., "title": ...}, ...]}``
-        """
-        body = request.get_json(silent=True) or {}
-        metrics: list[str] | None = body.get("metrics") or None
-
-        result = EvaluationService.get_nodes_for_metrics(
-            target=target,
-            target_type=target_type,
-            metrics=metrics,
-        )
-        if not metrics:
-            result = {
-                "all": [
-                    node
-                    for node in result.get("all", [])
-                    if node.get("type") not in EvaluationService.CONSOLE_DISABLED_CATEGORIES
-                ]
-            }
-        else:
-            result = {
-                metric: nodes
-                for metric, nodes in result.items()
-                if metric not in EvaluationService.CONSOLE_DISABLED_METRICS
-            }
-        return result
-
-
-@console_ns.route("/evaluation/available-metrics")
-class EvaluationAvailableMetricsApi(Resource):
-    @console_ns.doc("get_available_evaluation_metrics")
-    @console_ns.response(200, "Available metrics list")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self):
-        """Return the centrally-defined list of evaluation metrics."""
-        return {
-            "metrics": [
-                metric
-                for metric in EvaluationService.get_available_metrics()
-                if metric not in EvaluationService.CONSOLE_DISABLED_METRICS
-            ]
-        }
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/files/<uuid:file_id>")
-class EvaluationFileDownloadApi(Resource):
-    @console_ns.doc("download_evaluation_file")
-    @console_ns.response(200, "File download URL generated successfully")
-    @console_ns.response(404, "Target or file not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def get(self, target: Union[App, CustomizedSnippet], target_type: str, file_id: str):
-        """
-        Download evaluation test file or result file.
-
-        Looks up the specified file, verifies it belongs to the same tenant,
-        and returns file info and download URL.
-        """
-        file_id = str(file_id)
-        _, current_tenant_id = current_account_with_tenant()
-
-        with Session(db.engine, expire_on_commit=False) as session:
-            stmt = select(UploadFile).where(
-                UploadFile.id == file_id,
-                UploadFile.tenant_id == current_tenant_id,
-            )
-            upload_file = session.execute(stmt).scalar_one_or_none()
-
-        if not upload_file:
-            raise NotFound("File not found")
-
-        download_url = file_helpers.get_signed_file_url(upload_file_id=upload_file.id, as_attachment=True)
-
-        return {
-            "id": upload_file.id,
-            "name": upload_file.name,
-            "size": upload_file.size,
-            "extension": upload_file.extension,
-            "mime_type": upload_file.mime_type,
-            "created_at": int(upload_file.created_at.timestamp()) if upload_file.created_at else None,
-            "download_url": download_url,
-        }
-
-
-@console_ns.route("/<string:evaluate_target_type>/<uuid:evaluate_target_id>/evaluation/version")
-class EvaluationVersionApi(Resource):
-    @console_ns.doc("get_evaluation_version_detail")
-    @console_ns.expect(console_ns.models.get(VersionQuery.__name__))
-    @console_ns.response(200, "Version details retrieved successfully")
-    @console_ns.response(404, "Target or version not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @get_evaluation_target
-    def get(self, target: Union[App, CustomizedSnippet], target_type: str):
-        """
-        Get evaluation target version details.
-
-        Returns the workflow graph for the specified version.
-        """
-        version = request.args.get("version")
-
-        if not version:
-            return {"message": "version parameter is required"}, 400
-
-        graph = {}
-        if target_type == EvaluationTargetType.SNIPPETS.value and isinstance(target, CustomizedSnippet):
-            graph = target.graph_dict
-
-        return {
-            "graph": graph,
-        }
-
-
-@console_ns.route("/workspaces/current/available-evaluation-workflows")
-class AvailableEvaluationWorkflowsApi(Resource):
-    @console_ns.expect(console_ns.models[WorkflowListQuery.__name__])
-    @console_ns.doc("list_available_evaluation_workflows")
-    @console_ns.doc(description="List published evaluation workflows in the current workspace (all apps)")
-    @console_ns.response(
-        200,
-        "Available evaluation workflows retrieved",
-        available_evaluation_workflow_pagination_model,
-    )
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def get(self):
-        """List published evaluation-type workflows for the current tenant (cross-app)."""
-        current_user, current_tenant_id = current_account_with_tenant()
-
-        args = WorkflowListQuery.model_validate(request.args.to_dict(flat=True))  # type: ignore
-        page = args.page
-        limit = args.limit
-        user_id = args.user_id
-        named_only = args.named_only
-        keyword = args.keyword
-
-        if user_id and user_id != current_user.id:
-            raise Forbidden()
-
-        workflow_service = WorkflowService()
-        with Session(db.engine) as session:
-            workflows, has_more = workflow_service.list_published_evaluation_workflows(
-                session=session,
-                tenant_id=current_tenant_id,
-                page=page,
-                limit=limit,
-                user_id=user_id,
-                named_only=named_only,
-                keyword=keyword,
-            )
-
-            app_ids = {w.app_id for w in workflows}
-            if app_ids:
-                apps = session.scalars(select(App).where(App.id.in_(app_ids))).all()
-                app_names = {a.id: a.name for a in apps}
-            else:
-                app_names = {}
-
-        items = []
-        for wf in workflows:
-            items.append(
-                {
-                    "id": wf.id,
-                    "app_id": wf.app_id,
-                    "app_name": app_names.get(wf.app_id, ""),
-                    "type": wf.type.value,
-                    "kind": wf.kind_or_standard,
-                    "version": wf.version,
-                    "marked_name": wf.marked_name,
-                    "marked_comment": wf.marked_comment,
-                    "hash": wf.unique_hash,
-                    "created_by": wf.created_by_account,
-                    "created_at": wf.created_at,
-                    "updated_by": wf.updated_by_account,
-                    "updated_at": wf.updated_at,
-                }
-            )
-
-        return (
-            marshal(
-                {"items": items, "page": page, "limit": limit, "has_more": has_more},
-                available_evaluation_workflow_pagination_fields,
-            ),
-            200,
-        )
-
-
-@console_ns.route("/workspaces/current/evaluation-workflows/<string:workflow_id>/associated-targets")
-class EvaluationWorkflowAssociatedTargetsApi(Resource):
-    @console_ns.doc("list_evaluation_workflow_associated_targets")
-    @console_ns.doc(
-        description="List targets (apps / snippets / knowledge bases) that use the given workflow as customized metrics"
-    )
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def get(self, workflow_id: str):
-        """Return all evaluation targets that reference this workflow as customized metrics."""
-        _, current_tenant_id = current_account_with_tenant()
-
-        with Session(db.engine) as session:
-            configs = EvaluationService.list_targets_by_customized_workflow(
-                session=session,
-                tenant_id=current_tenant_id,
-                customized_workflow_id=workflow_id,
-            )
-
-            target_ids_by_type: dict[str, list[str]] = {}
-            for cfg in configs:
-                target_ids_by_type.setdefault(cfg.target_type, []).append(cfg.target_id)
-
-            app_names: dict[str, str] = {}
-            if EvaluationTargetType.APPS.value in target_ids_by_type:
-                apps = session.scalars(
-                    select(App).where(App.id.in_(target_ids_by_type[EvaluationTargetType.APPS.value]))
-                ).all()
-                app_names = {a.id: a.name for a in apps}
-
-            snippet_names: dict[str, str] = {}
-            if "snippets" in target_ids_by_type:
-                snippets = session.scalars(
-                    select(CustomizedSnippet).where(CustomizedSnippet.id.in_(target_ids_by_type["snippets"]))
-                ).all()
-                snippet_names = {s.id: s.name for s in snippets}
-
-            dataset_names: dict[str, str] = {}
-            if "knowledge_base" in target_ids_by_type:
-                datasets = session.scalars(
-                    select(Dataset).where(Dataset.id.in_(target_ids_by_type["knowledge_base"]))
-                ).all()
-                dataset_names = {d.id: d.name for d in datasets}
-
-        items = []
-        for cfg in configs:
-            name = ""
-            if cfg.target_type == EvaluationTargetType.APPS.value:
-                name = app_names.get(cfg.target_id, "")
-            elif cfg.target_type == EvaluationTargetType.SNIPPETS.value:
-                name = snippet_names.get(cfg.target_id, "")
-            elif cfg.target_type == "knowledge_base":
-                name = dataset_names.get(cfg.target_id, "")
-
-            items.append(
-                {
-                    "target_type": cfg.target_type,
-                    "target_id": cfg.target_id,
-                    "target_name": name,
-                }
-            )
-
-        return {"items": items}, 200
-
-
-# ---- Serialization Helpers ----
-
-
-def _serialize_evaluation_run(run: EvaluationRun) -> dict[str, object]:
-    return {
-        "id": run.id,
-        "tenant_id": run.tenant_id,
-        "target_type": run.target_type,
-        "target_id": run.target_id,
-        "evaluation_config_id": run.evaluation_config_id,
-        "status": run.status,
-        "dataset_file_id": run.dataset_file_id,
-        "result_file_id": run.result_file_id,
-        "total_items": run.total_items,
-        "completed_items": run.completed_items,
-        "failed_items": run.failed_items,
-        "progress": run.progress,
-        "metrics_summary": run.metrics_summary_dict,
-        "error": run.error,
-        "created_by": run.created_by,
-        "started_at": int(run.started_at.timestamp()) if run.started_at else None,
-        "completed_at": int(run.completed_at.timestamp()) if run.completed_at else None,
-        "created_at": int(run.created_at.timestamp()) if run.created_at else None,
-    }
-
-
-def _serialize_evaluation_run_item(item: EvaluationRunItem) -> dict[str, object]:
-    return {
-        "id": item.id,
-        "item_index": item.item_index,
-        "inputs": item.inputs_dict,
-        "expected_output": item.expected_output,
-        "actual_output": item.actual_output,
-        "metrics": item.metrics_list,
-        "judgment": item.judgment_dict,
-        "metadata": item.metadata_dict,
-        "error": item.error,
-        "overall_score": item.overall_score,
-    }

api/controllers/console/explore/installed_app.py

@@ -16,6 +16,7 @@ from extensions.ext_database import db
 from fields.base import ResponseModel
 from graphon.file import helpers as file_helpers
 from libs.datetime_utils import naive_utc_now
+from libs.helper import to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models import App, InstalledApp, RecommendedApp
 from models.model import IconType
@@ -105,9 +106,7 @@ class InstalledAppResponse(ResponseModel):
     @field_validator("last_used_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        if isinstance(value, datetime):
-            return int(value.timestamp())
-        return value
+        return to_timestamp(value)
 
 
 class InstalledAppListResponse(ResponseModel):

api/controllers/console/explore/recommended_app.py

@@ -64,28 +64,15 @@ class RecommendedAppListResponse(ResponseModel):
     categories: list[str]
 
 
-class LearnDifyAppListResponse(ResponseModel):
-    recommended_apps: list[RecommendedAppResponse]
-
-
 register_schema_models(
     console_ns,
     RecommendedAppsQuery,
     RecommendedAppInfoResponse,
     RecommendedAppResponse,
     RecommendedAppListResponse,
-    LearnDifyAppListResponse,
 )
 
 
-def _resolve_language(language: str | None) -> str:
-    if language and language in languages:
-        return language
-    if current_user and current_user.interface_language:
-        return current_user.interface_language
-    return languages[0]
-
-
 @console_ns.route("/explore/apps")
 class RecommendedAppListApi(Resource):
     @console_ns.doc(params=query_params_from_model(RecommendedAppsQuery))
@@ -95,7 +82,13 @@ class RecommendedAppListApi(Resource):
     def get(self):
         # language args
         args = RecommendedAppsQuery.model_validate(request.args.to_dict(flat=True))
-        language_prefix = _resolve_language(args.language)
+        language = args.language
+        if language and language in languages:
+            language_prefix = language
+        elif current_user and current_user.interface_language:
+            language_prefix = current_user.interface_language
+        else:
+            language_prefix = languages[0]
 
         return RecommendedAppListResponse.model_validate(
             RecommendedAppService.get_recommended_apps_and_categories(language_prefix),
@@ -103,22 +96,6 @@ class RecommendedAppListApi(Resource):
         ).model_dump(mode="json")
 
 
-@console_ns.route("/explore/apps/learn-dify")
-class LearnDifyAppListApi(Resource):
-    @console_ns.doc(params=query_params_from_model(RecommendedAppsQuery))
-    @console_ns.response(200, "Success", console_ns.models[LearnDifyAppListResponse.__name__])
-    @login_required
-    @account_initialization_required
-    def get(self):
-        args = RecommendedAppsQuery.model_validate(request.args.to_dict(flat=True))
-        language_prefix = _resolve_language(args.language)
-
-        return LearnDifyAppListResponse.model_validate(
-            RecommendedAppService.get_learn_dify_apps(language_prefix),
-            from_attributes=True,
-        ).model_dump(mode="json")
-
-
 @console_ns.route("/explore/apps/<uuid:app_id>")
 class RecommendedAppApi(Resource):
     @login_required

api/controllers/console/extension.py

@@ -7,6 +7,7 @@ from pydantic import BaseModel, Field, TypeAdapter, field_validator
 
 from constants import HIDDEN_VALUE
 from fields.base import ResponseModel
+from libs.helper import to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models.api_based_extension import APIBasedExtension
 from services.api_based_extension_service import APIBasedExtensionService
@@ -40,12 +41,6 @@ def _mask_api_key(api_key: str) -> str:
     return api_key[:3] + "******" + api_key[-3:]
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 class APIBasedExtensionResponse(ResponseModel):
     id: str
     name: str
@@ -61,7 +56,7 @@ class APIBasedExtensionResponse(ResponseModel):
     @field_validator("created_at", mode="before")
     @classmethod
     def _normalize_created_at(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 register_schema_models(console_ns, APIBasedExtensionPayload, CodeBasedExtensionResponse, APIBasedExtensionResponse)

api/controllers/console/files.py

@@ -105,7 +105,8 @@ class FilePreviewApi(Resource):
     @account_initialization_required
     def get(self, file_id):
         file_id = str(file_id)
-        text = FileService(db.engine).get_file_preview(file_id)
+        _, tenant_id = current_account_with_tenant()
+        text = FileService(db.engine).get_file_preview(file_id, tenant_id)
         return {"content": text}
 
 

api/controllers/console/snippets/payloads.py

@@ -1,142 +0,0 @@
-from typing import Any, Literal
-
-from pydantic import BaseModel, Field, field_validator
-
-
-class SnippetListQuery(BaseModel):
-    """Query parameters for listing snippets."""
-
-    page: int = Field(default=1, ge=1, le=99999)
-    limit: int = Field(default=20, ge=1, le=100)
-    keyword: str | None = None
-    is_published: bool | None = Field(default=None, description="Filter by published status")
-    creators: list[str] | None = Field(default=None, description="Filter by creator account IDs")
-
-    @field_validator("creators", mode="before")
-    @classmethod
-    def parse_creators(cls, value: object) -> list[str] | None:
-        """Normalize creators filter from query string or list input."""
-        if value is None:
-            return None
-        if isinstance(value, str):
-            return [creator.strip() for creator in value.split(",") if creator.strip()] or None
-        if isinstance(value, list):
-            return [str(creator).strip() for creator in value if str(creator).strip()] or None
-        return None
-
-
-class IconInfo(BaseModel):
-    """Icon information model."""
-
-    icon: str | None = None
-    icon_type: Literal["emoji", "image"] | None = None
-    icon_background: str | None = None
-    icon_url: str | None = None
-
-
-class InputFieldDefinition(BaseModel):
-    """Input field definition for snippet parameters."""
-
-    default: str | None = None
-    hint: bool | None = None
-    label: str | None = None
-    max_length: int | None = None
-    options: list[str] | None = None
-    placeholder: str | None = None
-    required: bool | None = None
-    type: str | None = None  # e.g., "text-input"
-
-
-class CreateSnippetPayload(BaseModel):
-    """Payload for creating a new snippet."""
-
-    name: str = Field(..., min_length=1, max_length=255)
-    description: str | None = Field(default=None, max_length=2000)
-    type: Literal["node", "group"] = "node"
-    icon_info: IconInfo | None = None
-    graph: dict[str, Any] | None = None
-    input_fields: list[InputFieldDefinition] | None = Field(default_factory=list)
-
-
-class UpdateSnippetPayload(BaseModel):
-    """Payload for updating a snippet."""
-
-    name: str | None = Field(default=None, min_length=1, max_length=255)
-    description: str | None = Field(default=None, max_length=2000)
-    icon_info: IconInfo | None = None
-
-
-class SnippetDraftSyncPayload(BaseModel):
-    """Payload for syncing snippet draft workflow."""
-
-    graph: dict[str, Any]
-    hash: str | None = None
-    conversation_variables: list[dict[str, Any]] | None = Field(
-        default=None,
-        description="Ignored. Snippet workflows do not persist conversation variables.",
-    )
-    input_fields: list[dict[str, Any]] | None = None
-
-
-class SnippetWorkflowListQuery(BaseModel):
-    """Query parameters for listing snippet published workflows."""
-
-    page: int = Field(default=1, ge=1, le=99999)
-    limit: int = Field(default=10, ge=1, le=100)
-
-
-class WorkflowRunQuery(BaseModel):
-    """Query parameters for workflow runs."""
-
-    last_id: str | None = None
-    limit: int = Field(default=20, ge=1, le=100)
-
-
-class SnippetDraftRunPayload(BaseModel):
-    """Payload for running snippet draft workflow."""
-
-    inputs: dict[str, Any]
-    files: list[dict[str, Any]] | None = None
-
-
-class SnippetDraftNodeRunPayload(BaseModel):
-    """Payload for running a single node in snippet draft workflow."""
-
-    inputs: dict[str, Any]
-    query: str = ""
-    files: list[dict[str, Any]] | None = None
-
-
-class SnippetIterationNodeRunPayload(BaseModel):
-    """Payload for running an iteration node in snippet draft workflow."""
-
-    inputs: dict[str, Any] | None = None
-
-
-class SnippetLoopNodeRunPayload(BaseModel):
-    """Payload for running a loop node in snippet draft workflow."""
-
-    inputs: dict[str, Any] | None = None
-
-
-class PublishWorkflowPayload(BaseModel):
-    """Payload for publishing snippet workflow."""
-
-    knowledge_base_setting: dict[str, Any] | None = None
-
-
-class SnippetImportPayload(BaseModel):
-    """Payload for importing snippet from DSL."""
-
-    mode: str = Field(..., description="Import mode: yaml-content or yaml-url")
-    yaml_content: str | None = Field(default=None, description="YAML content (required for yaml-content mode)")
-    yaml_url: str | None = Field(default=None, description="YAML URL (required for yaml-url mode)")
-    name: str | None = Field(default=None, description="Override snippet name")
-    description: str | None = Field(default=None, description="Override snippet description")
-    snippet_id: str | None = Field(default=None, description="Snippet ID to update (optional)")
-
-
-class IncludeSecretQuery(BaseModel):
-    """Query parameter for including secret variables in export."""
-
-    include_secret: str = Field(default="false", description="Whether to include secret variables")

api/controllers/console/snippets/snippet_workflow.py

@@ -1,617 +0,0 @@
-# import logging
-# from collections.abc import Callable
-# from functools import wraps
-
-# from flask import request
-# from flask_restx import Resource, fields, marshal, marshal_with
-# from sqlalchemy.orm import Session
-# from werkzeug.exceptions import BadRequest, InternalServerError, NotFound
-
-# from controllers.common.schema import register_schema_models
-# from controllers.console import console_ns
-# from controllers.console.app.error import DraftWorkflowNotExist, DraftWorkflowNotSync
-# from controllers.console.app.workflow import (
-#     RESTORE_SOURCE_WORKFLOW_MUST_BE_PUBLISHED_MESSAGE,
-#     workflow_model,
-#     workflow_pagination_model,
-# )
-# from controllers.console.app.workflow_run import (
-#     workflow_run_detail_model,
-#     workflow_run_node_execution_list_model,
-#     workflow_run_node_execution_model,
-#     workflow_run_pagination_model,
-# )
-# from controllers.console.snippets.payloads import (
-#     PublishWorkflowPayload,
-#     SnippetDraftNodeRunPayload,
-#     SnippetDraftRunPayload,
-#     SnippetDraftSyncPayload,
-#     SnippetIterationNodeRunPayload,
-#     SnippetLoopNodeRunPayload,
-#     SnippetWorkflowListQuery,
-#     WorkflowRunQuery,
-# )
-# from controllers.console.wraps import (
-#     account_initialization_required,
-#     edit_permission_required,
-#     setup_required,
-# )
-# from core.app.apps.base_app_queue_manager import AppQueueManager
-# from core.app.entities.app_invoke_entities import InvokeFrom
-# from extensions.ext_database import db
-# from extensions.ext_redis import redis_client
-# from graphon.graph_engine.manager import GraphEngineManager
-# from libs import helper
-# from libs.helper import TimestampField
-# from libs.login import current_account_with_tenant, login_required
-# from models.snippet import CustomizedSnippet
-# from services.errors.app import IsDraftWorkflowError, WorkflowHashNotEqualError, WorkflowNotFoundError
-# from services.snippet_generate_service import SnippetGenerateService
-# from services.snippet_service import SnippetService
-
-# logger = logging.getLogger(__name__)
-
-# # Register Pydantic models with Swagger
-# register_schema_models(
-#     console_ns,
-#     SnippetDraftSyncPayload,
-#     SnippetDraftNodeRunPayload,
-#     SnippetDraftRunPayload,
-#     SnippetIterationNodeRunPayload,
-#     SnippetLoopNodeRunPayload,
-#     SnippetWorkflowListQuery,
-#     WorkflowRunQuery,
-#     PublishWorkflowPayload,
-# )
-
-
-# snippet_workflow_model = console_ns.clone("SnippetWorkflow", workflow_model, {
-#     "input_fields": fields.Raw(default=[]),
-# })
-
-
-# class SnippetNotFoundError(Exception):
-#     """Snippet not found error."""
-
-#     pass
-
-
-# def get_snippet[**P, R](view_func: Callable[P, R]) -> Callable[P, R]:
-#     """Decorator to fetch and validate snippet access."""
-
-#     @wraps(view_func)
-#     def decorated_view(*args: P.args, **kwargs: P.kwargs) -> R:
-#         if not kwargs.get("snippet_id"):
-#             raise ValueError("missing snippet_id in path parameters")
-
-#         _, current_tenant_id = current_account_with_tenant()
-
-#         snippet_id = str(kwargs.get("snippet_id"))
-#         del kwargs["snippet_id"]
-
-#         snippet = SnippetService.get_snippet_by_id(
-#             snippet_id=snippet_id,
-#             tenant_id=current_tenant_id,
-#         )
-
-#         if not snippet:
-#             raise NotFound("Snippet not found")
-
-#         kwargs["snippet"] = snippet
-
-#         return view_func(*args, **kwargs)
-
-#     return decorated_view
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft")
-# class SnippetDraftWorkflowApi(Resource):
-#     @console_ns.doc("get_snippet_draft_workflow")
-#     @console_ns.response(200, "Draft workflow retrieved successfully", snippet_workflow_model)
-#     @console_ns.response(404, "Snippet or draft workflow not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     @marshal_with(snippet_workflow_model)
-#     def get(self, snippet: CustomizedSnippet):
-#         """Get draft workflow for snippet."""
-#         snippet_service = SnippetService()
-#         workflow = snippet_service.get_draft_workflow(snippet=snippet)
-
-#         if not workflow:
-#             raise DraftWorkflowNotExist()
-
-#         db.session.expunge(workflow)
-#         workflow.conversation_variables = []
-#         workflow.input_fields = snippet.input_fields_list
-#         return workflow
-
-#     @console_ns.doc("sync_snippet_draft_workflow")
-#     @console_ns.expect(console_ns.models.get(SnippetDraftSyncPayload.__name__))
-#     @console_ns.response(200, "Draft workflow synced successfully")
-#     @console_ns.response(400, "Hash mismatch")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet):
-#         """Sync draft workflow for snippet."""
-#         current_user, _ = current_account_with_tenant()
-
-#         payload = SnippetDraftSyncPayload.model_validate(console_ns.payload or {})
-
-#         try:
-#             snippet_service = SnippetService()
-#             workflow = snippet_service.sync_draft_workflow(
-#                 snippet=snippet,
-#                 graph=payload.graph,
-#                 unique_hash=payload.hash,
-#                 account=current_user,
-#                 input_fields=payload.input_fields,
-#             )
-#         except WorkflowHashNotEqualError:
-#             raise DraftWorkflowNotSync()
-#         except ValueError as e:
-#             return {"message": str(e)}, 400
-
-#         return {
-#             "result": "success",
-#             "hash": workflow.unique_hash,
-#             "updated_at": TimestampField().format(workflow.updated_at or workflow.created_at),
-#         }
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/config")
-# class SnippetDraftConfigApi(Resource):
-#     @console_ns.doc("get_snippet_draft_config")
-#     @console_ns.response(200, "Draft config retrieved successfully")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def get(self, snippet: CustomizedSnippet):
-#         """Get snippet draft workflow configuration limits."""
-#         return {
-#             "parallel_depth_limit": 3,
-#         }
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/publish")
-# class SnippetPublishedWorkflowApi(Resource):
-#     @console_ns.doc("get_snippet_published_workflow")
-#     @console_ns.response(200, "Published workflow retrieved successfully", snippet_workflow_model)
-#     @console_ns.response(404, "Snippet not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     @marshal_with(snippet_workflow_model)
-#     def get(self, snippet: CustomizedSnippet):
-#         """Get published workflow for snippet."""
-#         if not snippet.is_published:
-#             return None
-
-#         snippet_service = SnippetService()
-#         workflow = snippet_service.get_published_workflow(snippet=snippet)
-
-#         if workflow:
-#             workflow.input_fields = snippet.input_fields_list
-
-#         return workflow
-
-#     @console_ns.doc("publish_snippet_workflow")
-#     @console_ns.expect(console_ns.models.get(PublishWorkflowPayload.__name__))
-#     @console_ns.response(200, "Workflow published successfully")
-#     @console_ns.response(400, "No draft workflow found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet):
-#         """Publish snippet workflow."""
-#         current_user, _ = current_account_with_tenant()
-#         snippet_service = SnippetService()
-
-#         with Session(db.engine) as session:
-#             snippet = session.merge(snippet)
-#             try:
-#                 workflow = snippet_service.publish_workflow(
-#                     session=session,
-#                     snippet=snippet,
-#                     account=current_user,
-#                 )
-#                 workflow_created_at = TimestampField().format(workflow.created_at)
-#                 session.commit()
-#             except ValueError as e:
-#                 return {"message": str(e)}, 400
-
-#         return {
-#             "result": "success",
-#             "created_at": workflow_created_at,
-#         }
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/default-workflow-block-configs")
-# class SnippetDefaultBlockConfigsApi(Resource):
-#     @console_ns.doc("get_snippet_default_block_configs")
-#     @console_ns.response(200, "Default block configs retrieved successfully")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def get(self, snippet: CustomizedSnippet):
-#         """Get default block configurations for snippet workflow."""
-#         snippet_service = SnippetService()
-#         return snippet_service.get_default_block_configs()
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows")
-# class SnippetPublishedAllWorkflowApi(Resource):
-#     @console_ns.expect(console_ns.models[SnippetWorkflowListQuery.__name__])
-#     @console_ns.doc("get_all_snippet_published_workflows")
-#     @console_ns.doc(description="Get all published workflows for a snippet")
-#     @console_ns.doc(params={"snippet_id": "Snippet ID"})
-#     @console_ns.response(200, "Published workflows retrieved successfully", workflow_pagination_model)
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def get(self, snippet: CustomizedSnippet):
-#         """Get all published workflow versions for snippet."""
-#         args = SnippetWorkflowListQuery.model_validate(request.args.to_dict(flat=True))
-
-#         snippet_service = SnippetService()
-#         with Session(db.engine) as session:
-#             workflows, has_more = snippet_service.get_all_published_workflows(
-#                 session=session,
-#                 snippet=snippet,
-#                 page=args.page,
-#                 limit=args.limit,
-#             )
-#             serialized_workflows = marshal(workflows, workflow_model)
-
-#         return {
-#             "items": serialized_workflows,
-#             "page": args.page,
-#             "limit": args.limit,
-#             "has_more": has_more,
-#         }
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/<string:workflow_id>/restore")
-# class SnippetDraftWorkflowRestoreApi(Resource):
-#     @console_ns.doc("restore_snippet_workflow_to_draft")
-#     @console_ns.doc(description="Restore a published snippet workflow version into the draft workflow")
-#     @console_ns.doc(params={"snippet_id": "Snippet ID", "workflow_id": "Published workflow ID"})
-#     @console_ns.response(200, "Workflow restored successfully")
-#     @console_ns.response(400, "Source workflow must be published")
-#     @console_ns.response(404, "Workflow not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet, workflow_id: str):
-#         """Restore a published snippet workflow version into the draft workflow."""
-#         current_user, _ = current_account_with_tenant()
-#         snippet_service = SnippetService()
-
-#         try:
-#             workflow = snippet_service.restore_published_workflow_to_draft(
-#                 snippet=snippet,
-#                 workflow_id=workflow_id,
-#                 account=current_user,
-#             )
-#         except IsDraftWorkflowError as exc:
-#             raise BadRequest(RESTORE_SOURCE_WORKFLOW_MUST_BE_PUBLISHED_MESSAGE) from exc
-#         except WorkflowNotFoundError as exc:
-#             raise NotFound(str(exc)) from exc
-#         except ValueError as exc:
-#             raise BadRequest(str(exc)) from exc
-
-#         return {
-#             "result": "success",
-#             "hash": workflow.unique_hash,
-#             "updated_at": TimestampField().format(workflow.updated_at or workflow.created_at),
-#         }
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflow-runs")
-# class SnippetWorkflowRunsApi(Resource):
-#     @console_ns.doc("list_snippet_workflow_runs")
-#     @console_ns.response(200, "Workflow runs retrieved successfully", workflow_run_pagination_model)
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @marshal_with(workflow_run_pagination_model)
-#     def get(self, snippet: CustomizedSnippet):
-#         """List workflow runs for snippet."""
-#         query = WorkflowRunQuery.model_validate(
-#             {
-#                 "last_id": request.args.get("last_id"),
-#                 "limit": request.args.get("limit", type=int, default=20),
-#             }
-#         )
-#         args = {
-#             "last_id": query.last_id,
-#             "limit": query.limit,
-#         }
-
-#         snippet_service = SnippetService()
-#         result = snippet_service.get_snippet_workflow_runs(snippet=snippet, args=args)
-
-#         return result
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflow-runs/<uuid:run_id>")
-# class SnippetWorkflowRunDetailApi(Resource):
-#     @console_ns.doc("get_snippet_workflow_run_detail")
-#     @console_ns.response(200, "Workflow run detail retrieved successfully", workflow_run_detail_model)
-#     @console_ns.response(404, "Workflow run not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @marshal_with(workflow_run_detail_model)
-#     def get(self, snippet: CustomizedSnippet, run_id):
-#         """Get workflow run detail for snippet."""
-#         run_id = str(run_id)
-
-#         snippet_service = SnippetService()
-#         workflow_run = snippet_service.get_snippet_workflow_run(snippet=snippet, run_id=run_id)
-
-#         if not workflow_run:
-#             raise NotFound("Workflow run not found")
-
-#         return workflow_run
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflow-runs/<uuid:run_id>/node-executions")
-# class SnippetWorkflowRunNodeExecutionsApi(Resource):
-#     @console_ns.doc("list_snippet_workflow_run_node_executions")
-#     @console_ns.response(200, "Node executions retrieved successfully", workflow_run_node_execution_list_model)
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @marshal_with(workflow_run_node_execution_list_model)
-#     def get(self, snippet: CustomizedSnippet, run_id):
-#         """List node executions for a workflow run."""
-#         run_id = str(run_id)
-
-#         snippet_service = SnippetService()
-#         node_executions = snippet_service.get_snippet_workflow_run_node_executions(
-#             snippet=snippet,
-#             run_id=run_id,
-#         )
-
-#         return {"data": node_executions}
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/nodes/<string:node_id>/run")
-# class SnippetDraftNodeRunApi(Resource):
-#     @console_ns.doc("run_snippet_draft_node")
-#     @console_ns.doc(description="Run a single node in snippet draft workflow (single-step debugging)")
-#     @console_ns.doc(params={"snippet_id": "Snippet ID", "node_id": "Node ID"})
-#     @console_ns.expect(console_ns.models.get(SnippetDraftNodeRunPayload.__name__))
-#     @console_ns.response(200, "Node run completed successfully", workflow_run_node_execution_model)
-#     @console_ns.response(404, "Snippet or draft workflow not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @marshal_with(workflow_run_node_execution_model)
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet, node_id: str):
-#         """
-#         Run a single node in snippet draft workflow.
-
-#         Executes a specific node with provided inputs for single-step debugging.
-#         Returns the node execution result including status, outputs, and timing.
-#         """
-#         current_user, _ = current_account_with_tenant()
-#         payload = SnippetDraftNodeRunPayload.model_validate(console_ns.payload or {})
-
-#         user_inputs = payload.inputs
-
-#         # Get draft workflow for file parsing
-#         snippet_service = SnippetService()
-#         draft_workflow = snippet_service.get_draft_workflow(snippet=snippet)
-#         if not draft_workflow:
-#             raise NotFound("Draft workflow not found")
-
-#         files = SnippetGenerateService.parse_files(draft_workflow, payload.files)
-
-#         workflow_node_execution = SnippetGenerateService.run_draft_node(
-#             snippet=snippet,
-#             node_id=node_id,
-#             user_inputs=user_inputs,
-#             account=current_user,
-#             query=payload.query,
-#             files=files,
-#         )
-
-#         return workflow_node_execution
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/nodes/<string:node_id>/last-run")
-# class SnippetDraftNodeLastRunApi(Resource):
-#     @console_ns.doc("get_snippet_draft_node_last_run")
-#     @console_ns.doc(description="Get last run result for a node in snippet draft workflow")
-#     @console_ns.doc(params={"snippet_id": "Snippet ID", "node_id": "Node ID"})
-#     @console_ns.response(200, "Node last run retrieved successfully", workflow_run_node_execution_model)
-#     @console_ns.response(404, "Snippet, draft workflow, or node last run not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @marshal_with(workflow_run_node_execution_model)
-#     def get(self, snippet: CustomizedSnippet, node_id: str):
-#         """
-#         Get the last run result for a specific node in snippet draft workflow.
-
-#         Returns the most recent execution record for the given node,
-#         including status, inputs, outputs, and timing information.
-#         """
-#         snippet_service = SnippetService()
-#         draft_workflow = snippet_service.get_draft_workflow(snippet=snippet)
-#         if not draft_workflow:
-#             raise NotFound("Draft workflow not found")
-
-#         node_exec = snippet_service.get_snippet_node_last_run(
-#             snippet=snippet,
-#             workflow=draft_workflow,
-#             node_id=node_id,
-#         )
-#         if node_exec is None:
-#             raise NotFound("Node last run not found")
-
-#         return node_exec
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/iteration/nodes/<string:node_id>/run")
-# class SnippetDraftRunIterationNodeApi(Resource):
-#     @console_ns.doc("run_snippet_draft_iteration_node")
-#     @console_ns.doc(description="Run draft workflow iteration node for snippet")
-#     @console_ns.doc(params={"snippet_id": "Snippet ID", "node_id": "Node ID"})
-#     @console_ns.expect(console_ns.models.get(SnippetIterationNodeRunPayload.__name__))
-#     @console_ns.response(200, "Iteration node run started successfully (SSE stream)")
-#     @console_ns.response(404, "Snippet or draft workflow not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet, node_id: str):
-#         """
-#         Run a draft workflow iteration node for snippet.
-
-#         Iteration nodes execute their internal sub-graph multiple times over an input list.
-#         Returns an SSE event stream with iteration progress and results.
-#         """
-#         current_user, _ = current_account_with_tenant()
-#         args = SnippetIterationNodeRunPayload.model_validate(console_ns.payload or {}).model_dump(exclude_none=True)
-
-#         try:
-#             response = SnippetGenerateService.generate_single_iteration(
-#                 snippet=snippet, user=current_user, node_id=node_id, args=args, streaming=True
-#             )
-
-#             return helper.compact_generate_response(response)
-#         except ValueError as e:
-#             raise e
-#         except Exception:
-#             logger.exception("internal server error.")
-#             raise InternalServerError()
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/loop/nodes/<string:node_id>/run")
-# class SnippetDraftRunLoopNodeApi(Resource):
-#     @console_ns.doc("run_snippet_draft_loop_node")
-#     @console_ns.doc(description="Run draft workflow loop node for snippet")
-#     @console_ns.doc(params={"snippet_id": "Snippet ID", "node_id": "Node ID"})
-#     @console_ns.expect(console_ns.models.get(SnippetLoopNodeRunPayload.__name__))
-#     @console_ns.response(200, "Loop node run started successfully (SSE stream)")
-#     @console_ns.response(404, "Snippet or draft workflow not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet, node_id: str):
-#         """
-#         Run a draft workflow loop node for snippet.
-
-#         Loop nodes execute their internal sub-graph repeatedly until a condition is met.
-#         Returns an SSE event stream with loop progress and results.
-#         """
-#         current_user, _ = current_account_with_tenant()
-#         args = SnippetLoopNodeRunPayload.model_validate(console_ns.payload or {})
-
-#         try:
-#             response = SnippetGenerateService.generate_single_loop(
-#                 snippet=snippet, user=current_user, node_id=node_id, args=args, streaming=True
-#             )
-
-#             return helper.compact_generate_response(response)
-#         except ValueError as e:
-#             raise e
-#         except Exception:
-#             logger.exception("internal server error.")
-#             raise InternalServerError()
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/run")
-# class SnippetDraftWorkflowRunApi(Resource):
-#     @console_ns.doc("run_snippet_draft_workflow")
-#     @console_ns.expect(console_ns.models.get(SnippetDraftRunPayload.__name__))
-#     @console_ns.response(200, "Draft workflow run started successfully (SSE stream)")
-#     @console_ns.response(404, "Snippet or draft workflow not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet):
-#         """
-#         Run draft workflow for snippet.
-
-#         Executes the snippet's draft workflow with the provided inputs
-#         and returns an SSE event stream with execution progress and results.
-#         """
-#         current_user, _ = current_account_with_tenant()
-
-#         payload = SnippetDraftRunPayload.model_validate(console_ns.payload or {})
-#         args = payload.model_dump(exclude_none=True)
-
-#         try:
-#             response = SnippetGenerateService.generate(
-#                 snippet=snippet,
-#                 user=current_user,
-#                 args=args,
-#                 invoke_from=InvokeFrom.DEBUGGER,
-#                 streaming=True,
-#             )
-
-#             return helper.compact_generate_response(response)
-#         except ValueError as e:
-#             raise e
-#         except Exception:
-#             logger.exception("internal server error.")
-#             raise InternalServerError()
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflow-runs/tasks/<string:task_id>/stop")
-# class SnippetWorkflowTaskStopApi(Resource):
-#     @console_ns.doc("stop_snippet_workflow_task")
-#     @console_ns.response(200, "Task stopped successfully")
-#     @console_ns.response(404, "Snippet not found")
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     def post(self, snippet: CustomizedSnippet, task_id: str):
-#         """
-#         Stop a running snippet workflow task.
-
-#         Uses both the legacy stop flag mechanism and the graph engine
-#         command channel for backward compatibility.
-#         """
-#         # Stop using both mechanisms for backward compatibility
-#         # Legacy stop flag mechanism (without user check)
-#         AppQueueManager.set_stop_flag_no_user_check(task_id)
-
-#         # New graph engine command channel mechanism
-#         GraphEngineManager(redis_client).send_stop_command(task_id)
-
-#         return {"result": "success"}

api/controllers/console/snippets/snippet_workflow_draft_variable.py

@@ -1,316 +0,0 @@
-# """
-# Snippet draft workflow variable APIs.
-
-# Mirrors console app routes under /apps/.../workflows/draft/variables for snippet scope,
-# using CustomizedSnippet.id as WorkflowDraftVariable.app_id (same invariant as snippet execution).
-
-# Snippet workflows do not expose system variables (`node_id == sys`) or conversation variables
-# (`node_id == conversation`): paginated list queries exclude those rows; single-variable GET/PATCH/DELETE/reset
-# reject them; `GET .../system-variables` and `GET .../conversation-variables` return empty lists for API parity.
-# Other routes mirror `workflow_draft_variable` app APIs under `/snippets/...`.
-# """
-
-# from collections.abc import Callable
-# from functools import wraps
-# from typing import Any
-
-# from flask import Response, request
-# from flask_restx import Resource, marshal, marshal_with
-# from sqlalchemy.orm import Session
-
-# from controllers.console import console_ns
-# from controllers.console.app.error import DraftWorkflowNotExist
-# from controllers.console.app.workflow_draft_variable import (
-#     WorkflowDraftVariableListQuery,
-#     WorkflowDraftVariableUpdatePayload,
-#     _ensure_variable_access,
-#     _file_access_controller,
-#     validate_node_id,
-#     workflow_draft_variable_list_model,
-#     workflow_draft_variable_list_without_value_model,
-#     workflow_draft_variable_model,
-# )
-# from controllers.console.snippets.snippet_workflow import get_snippet
-# from controllers.console.wraps import account_initialization_required, edit_permission_required, setup_required
-# from controllers.web.error import InvalidArgumentError, NotFoundError
-# from core.workflow.variable_prefixes import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID
-# from extensions.ext_database import db
-# from factories.file_factory import build_from_mapping, build_from_mappings
-# from factories.variable_factory import build_segment_with_type
-# from graphon.variables.types import SegmentType
-# from libs.login import current_user, login_required
-# from models.snippet import CustomizedSnippet
-# from models.workflow import WorkflowDraftVariable
-# from services.snippet_service import SnippetService
-# from services.workflow_draft_variable_service import WorkflowDraftVariableList, WorkflowDraftVariableService
-
-# _SNIPPET_EXCLUDED_DRAFT_VARIABLE_NODE_IDS: frozenset[str] = frozenset(
-#     {SYSTEM_VARIABLE_NODE_ID, CONVERSATION_VARIABLE_NODE_ID}
-# )
-
-
-# def _ensure_snippet_draft_variable_row_allowed(
-#     *,
-#     variable: WorkflowDraftVariable,
-#     variable_id: str,
-# ) -> None:
-#     """Snippet scope only supports canvas-node draft variables; treat sys/conversation rows as not found."""
-#     if variable.node_id in _SNIPPET_EXCLUDED_DRAFT_VARIABLE_NODE_IDS:
-#         raise NotFoundError(description=f"variable not found, id={variable_id}")
-
-
-# def _snippet_draft_var_prerequisite[**P, R](f: Callable[P, R]) -> Callable[P, R]:
-#     """Setup, auth, snippet resolution, and tenant edit permission (same stack as snippet workflow APIs)."""
-
-#     @setup_required
-#     @login_required
-#     @account_initialization_required
-#     @get_snippet
-#     @edit_permission_required
-#     @wraps(f)
-#     def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
-#         return f(*args, **kwargs)
-
-#     return wrapper
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/variables")
-# class SnippetWorkflowVariableCollectionApi(Resource):
-#     @console_ns.expect(console_ns.models[WorkflowDraftVariableListQuery.__name__])
-#     @console_ns.doc("get_snippet_workflow_variables")
-#     @console_ns.doc(description="List draft workflow variables without values (paginated, snippet scope)")
-#     @console_ns.response(
-#         200,
-#         "Workflow variables retrieved successfully",
-#         workflow_draft_variable_list_without_value_model,
-#     )
-#     @_snippet_draft_var_prerequisite
-#     @marshal_with(workflow_draft_variable_list_without_value_model)
-#     def get(self, snippet: CustomizedSnippet) -> WorkflowDraftVariableList:
-#         args = WorkflowDraftVariableListQuery.model_validate(request.args.to_dict(flat=True))  # type: ignore
-
-#         snippet_service = SnippetService()
-#         if snippet_service.get_draft_workflow(snippet=snippet) is None:
-#             raise DraftWorkflowNotExist()
-
-#         with Session(bind=db.engine, expire_on_commit=False) as session:
-#             draft_var_srv = WorkflowDraftVariableService(session=session)
-#             workflow_vars = draft_var_srv.list_variables_without_values(
-#                 app_id=snippet.id,
-#                 page=args.page,
-#                 limit=args.limit,
-#                 user_id=current_user.id,
-#                 exclude_node_ids=_SNIPPET_EXCLUDED_DRAFT_VARIABLE_NODE_IDS,
-#             )
-
-#         return workflow_vars
-
-#     @console_ns.doc("delete_snippet_workflow_variables")
-#     @console_ns.doc(description="Delete all draft workflow variables for the current user (snippet scope)")
-#     @console_ns.response(204, "Workflow variables deleted successfully")
-#     @_snippet_draft_var_prerequisite
-#     def delete(self, snippet: CustomizedSnippet) -> Response:
-#         draft_var_srv = WorkflowDraftVariableService(session=db.session())
-#         draft_var_srv.delete_user_workflow_variables(snippet.id, user_id=current_user.id)
-#         db.session.commit()
-#         return Response("", 204)
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/nodes/<string:node_id>/variables")
-# class SnippetNodeVariableCollectionApi(Resource):
-#     @console_ns.doc("get_snippet_node_variables")
-#     @console_ns.doc(description="Get variables for a specific node (snippet draft workflow)")
-#     @console_ns.response(200, "Node variables retrieved successfully", workflow_draft_variable_list_model)
-#     @_snippet_draft_var_prerequisite
-#     @marshal_with(workflow_draft_variable_list_model)
-#     def get(self, snippet: CustomizedSnippet, node_id: str) -> WorkflowDraftVariableList:
-#         validate_node_id(node_id)
-#         with Session(bind=db.engine, expire_on_commit=False) as session:
-#             draft_var_srv = WorkflowDraftVariableService(session=session)
-#             node_vars = draft_var_srv.list_node_variables(snippet.id, node_id, user_id=current_user.id)
-
-#         return node_vars
-
-#     @console_ns.doc("delete_snippet_node_variables")
-#     @console_ns.doc(description="Delete all variables for a specific node (snippet draft workflow)")
-#     @console_ns.response(204, "Node variables deleted successfully")
-#     @_snippet_draft_var_prerequisite
-#     def delete(self, snippet: CustomizedSnippet, node_id: str) -> Response:
-#         validate_node_id(node_id)
-#         srv = WorkflowDraftVariableService(db.session())
-#         srv.delete_node_variables(snippet.id, node_id, user_id=current_user.id)
-#         db.session.commit()
-#         return Response("", 204)
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/variables/<uuid:variable_id>")
-# class SnippetVariableApi(Resource):
-#     @console_ns.doc("get_snippet_workflow_variable")
-#     @console_ns.doc(description="Get a specific draft workflow variable (snippet scope)")
-#     @console_ns.response(200, "Variable retrieved successfully", workflow_draft_variable_model)
-#     @console_ns.response(404, "Variable not found")
-#     @_snippet_draft_var_prerequisite
-#     @marshal_with(workflow_draft_variable_model)
-#     def get(self, snippet: CustomizedSnippet, variable_id: str) -> WorkflowDraftVariable:
-#         draft_var_srv = WorkflowDraftVariableService(session=db.session())
-#         variable = _ensure_variable_access(
-#             variable=draft_var_srv.get_variable(variable_id=variable_id),
-#             app_id=snippet.id,
-#             variable_id=variable_id,
-#         )
-#         _ensure_snippet_draft_variable_row_allowed(variable=variable, variable_id=variable_id)
-#         return variable
-
-#     @console_ns.doc("update_snippet_workflow_variable")
-#     @console_ns.doc(description="Update a draft workflow variable (snippet scope)")
-#     @console_ns.expect(console_ns.models[WorkflowDraftVariableUpdatePayload.__name__])
-#     @console_ns.response(200, "Variable updated successfully", workflow_draft_variable_model)
-#     @console_ns.response(404, "Variable not found")
-#     @_snippet_draft_var_prerequisite
-#     @marshal_with(workflow_draft_variable_model)
-#     def patch(self, snippet: CustomizedSnippet, variable_id: str) -> WorkflowDraftVariable:
-#         draft_var_srv = WorkflowDraftVariableService(session=db.session())
-#         args_model = WorkflowDraftVariableUpdatePayload.model_validate(console_ns.payload or {})
-
-#         variable = _ensure_variable_access(
-#             variable=draft_var_srv.get_variable(variable_id=variable_id),
-#             app_id=snippet.id,
-#             variable_id=variable_id,
-#         )
-#         _ensure_snippet_draft_variable_row_allowed(variable=variable, variable_id=variable_id)
-
-#         new_name = args_model.name
-#         raw_value = args_model.value
-#         if new_name is None and raw_value is None:
-#             return variable
-
-#         new_value = None
-#         if raw_value is not None:
-#             if variable.value_type == SegmentType.FILE:
-#                 if not isinstance(raw_value, dict):
-#                     raise InvalidArgumentError(description=f"expected dict for file, got {type(raw_value)}")
-#                 raw_value = build_from_mapping(
-#                     mapping=raw_value,
-#                     tenant_id=snippet.tenant_id,
-#                     access_controller=_file_access_controller,
-#                 )
-#             elif variable.value_type == SegmentType.ARRAY_FILE:
-#                 if not isinstance(raw_value, list):
-#                     raise InvalidArgumentError(description=f"expected list for files, got {type(raw_value)}")
-#                 if len(raw_value) > 0 and not isinstance(raw_value[0], dict):
-#                     raise InvalidArgumentError(description=f"expected dict for files[0], got {type(raw_value)}")
-#                 raw_value = build_from_mappings(
-#                     mappings=raw_value,
-#                     tenant_id=snippet.tenant_id,
-#                     access_controller=_file_access_controller,
-#                 )
-#             new_value = build_segment_with_type(variable.value_type, raw_value)
-#         draft_var_srv.update_variable(variable, name=new_name, value=new_value)
-#         db.session.commit()
-#         return variable
-
-#     @console_ns.doc("delete_snippet_workflow_variable")
-#     @console_ns.doc(description="Delete a draft workflow variable (snippet scope)")
-#     @console_ns.response(204, "Variable deleted successfully")
-#     @console_ns.response(404, "Variable not found")
-#     @_snippet_draft_var_prerequisite
-#     def delete(self, snippet: CustomizedSnippet, variable_id: str) -> Response:
-#         draft_var_srv = WorkflowDraftVariableService(session=db.session())
-#         variable = _ensure_variable_access(
-#             variable=draft_var_srv.get_variable(variable_id=variable_id),
-#             app_id=snippet.id,
-#             variable_id=variable_id,
-#         )
-#         _ensure_snippet_draft_variable_row_allowed(variable=variable, variable_id=variable_id)
-#         draft_var_srv.delete_variable(variable)
-#         db.session.commit()
-#         return Response("", 204)
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/variables/<uuid:variable_id>/reset")
-# class SnippetVariableResetApi(Resource):
-#     @console_ns.doc("reset_snippet_workflow_variable")
-#     @console_ns.doc(description="Reset a draft workflow variable to its default value (snippet scope)")
-#     @console_ns.response(200, "Variable reset successfully", workflow_draft_variable_model)
-#     @console_ns.response(204, "Variable reset (no content)")
-#     @console_ns.response(404, "Variable not found")
-#     @_snippet_draft_var_prerequisite
-#     def put(self, snippet: CustomizedSnippet, variable_id: str) -> Response | Any:
-#         draft_var_srv = WorkflowDraftVariableService(session=db.session())
-#         snippet_service = SnippetService()
-#         draft_workflow = snippet_service.get_draft_workflow(snippet=snippet)
-#         if draft_workflow is None:
-#             raise NotFoundError(
-#                 f"Draft workflow not found, snippet_id={snippet.id}",
-#             )
-#         variable = _ensure_variable_access(
-#             variable=draft_var_srv.get_variable(variable_id=variable_id),
-#             app_id=snippet.id,
-#             variable_id=variable_id,
-#         )
-#         _ensure_snippet_draft_variable_row_allowed(variable=variable, variable_id=variable_id)
-
-#         resetted = draft_var_srv.reset_variable(draft_workflow, variable)
-#         db.session.commit()
-#         if resetted is None:
-#             return Response("", 204)
-#         return marshal(resetted, workflow_draft_variable_model)
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/conversation-variables")
-# class SnippetConversationVariableCollectionApi(Resource):
-#     @console_ns.doc("get_snippet_conversation_variables")
-#     @console_ns.doc(
-#         description="Conversation variables are not used in snippet workflows; returns an empty list for API parity"
-#     )
-#     @console_ns.response(200, "Conversation variables retrieved successfully", workflow_draft_variable_list_model)
-#     @_snippet_draft_var_prerequisite
-#     @marshal_with(workflow_draft_variable_list_model)
-#     def get(self, snippet: CustomizedSnippet) -> WorkflowDraftVariableList:
-#         return WorkflowDraftVariableList(variables=[])
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/system-variables")
-# class SnippetSystemVariableCollectionApi(Resource):
-#     @console_ns.doc("get_snippet_system_variables")
-#     @console_ns.doc(
-#         description="System variables are not used in snippet workflows; returns an empty list for API parity"
-#     )
-#     @console_ns.response(200, "System variables retrieved successfully", workflow_draft_variable_list_model)
-#     @_snippet_draft_var_prerequisite
-#     @marshal_with(workflow_draft_variable_list_model)
-#     def get(self, snippet: CustomizedSnippet) -> WorkflowDraftVariableList:
-#         return WorkflowDraftVariableList(variables=[])
-
-
-# @console_ns.route("/snippets/<uuid:snippet_id>/workflows/draft/environment-variables")
-# class SnippetEnvironmentVariableCollectionApi(Resource):
-#     @console_ns.doc("get_snippet_environment_variables")
-#     @console_ns.doc(description="Get environment variables from snippet draft workflow graph")
-#     @console_ns.response(200, "Environment variables retrieved successfully")
-#     @console_ns.response(404, "Draft workflow not found")
-#     @_snippet_draft_var_prerequisite
-#     def get(self, snippet: CustomizedSnippet) -> dict[str, list[dict[str, Any]]]:
-#         snippet_service = SnippetService()
-#         workflow = snippet_service.get_draft_workflow(snippet=snippet)
-#         if workflow is None:
-#             raise DraftWorkflowNotExist()
-
-#         env_vars_list: list[dict[str, Any]] = []
-#         for v in workflow.environment_variables:
-#             env_vars_list.append(
-#                 {
-#                     "id": v.id,
-#                     "type": "env",
-#                     "name": v.name,
-#                     "description": v.description,
-#                     "selector": v.selector,
-#                     "value_type": v.value_type.exposed_type().value,
-#                     "value": v.value,
-#                     "edited": False,
-#                     "visible": True,
-#                     "editable": True,
-#                 }
-#             )
-
-#         return {"items": env_vars_list}

api/controllers/console/tag/tags.py

@@ -25,6 +25,10 @@ class TagBasePayload(BaseModel):
     type: TagType = Field(description="Tag type")
 
 
+class TagUpdateRequestPayload(BaseModel):
+    name: str = Field(description="Tag name", min_length=1, max_length=50)
+
+
 class TagBindingPayload(BaseModel):
     tag_ids: list[str] = Field(description="Tag IDs to bind")
     target_id: str = Field(description="Target ID to bind tags to")
@@ -68,6 +72,7 @@ class TagResponse(ResponseModel):
 register_schema_models(
     console_ns,
     TagBasePayload,
+    TagUpdateRequestPayload,
     TagBindingPayload,
     TagBindingRemovePayload,
     TagListQueryParam,
@@ -118,7 +123,7 @@ class TagListApi(Resource):
 
 @console_ns.route("/tags/<uuid:tag_id>")
 class TagUpdateDeleteApi(Resource):
-    @console_ns.expect(console_ns.models[TagBasePayload.__name__])
+    @console_ns.expect(console_ns.models[TagUpdateRequestPayload.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -129,8 +134,8 @@ class TagUpdateDeleteApi(Resource):
         if not (current_user.has_edit_permission or current_user.is_dataset_editor):
             raise Forbidden()
 
-        payload = TagBasePayload.model_validate(console_ns.payload or {})
-        tag = TagService.update_tags(UpdateTagPayload(name=payload.name, type=payload.type), tag_id)
+        payload = TagUpdateRequestPayload.model_validate(console_ns.payload or {})
+        tag = TagService.update_tags(UpdateTagPayload(name=payload.name), tag_id)
 
         binding_count = TagService.get_tag_binding_count(tag_id)
 

api/controllers/console/workspace/account.py

@@ -42,7 +42,7 @@ from fields.base import ResponseModel
 from fields.member_fields import Account as AccountResponse
 from graphon.file import helpers as file_helpers
 from libs.datetime_utils import naive_utc_now
-from libs.helper import EmailStr, extract_remote_ip, timezone
+from libs.helper import EmailStr, extract_remote_ip, timezone, to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models import AccountIntegrate, InvitationCode
 from models.account import AccountStatus, InvitationCodeStatus
@@ -185,12 +185,6 @@ def _serialize_account(account) -> dict[str, Any]:
     return AccountResponse.model_validate(account, from_attributes=True).model_dump(mode="json")
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 class AccountIntegrateResponse(ResponseModel):
     provider: str
     created_at: int | None = None
@@ -200,7 +194,7 @@ class AccountIntegrateResponse(ResponseModel):
     @field_validator("created_at", mode="before")
     @classmethod
     def _normalize_created_at(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class AccountIntegrateListResponse(ResponseModel):
@@ -220,7 +214,7 @@ class EducationStatusResponse(ResponseModel):
     @field_validator("expire_at", mode="before")
     @classmethod
     def _normalize_expire_at(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class EducationAutocompleteResponse(ResponseModel):

api/controllers/console/workspace/members.py

@@ -30,14 +30,13 @@ from libs.helper import extract_remote_ip
 from libs.login import current_account_with_tenant, login_required
 from models.account import Account, TenantAccountRole
 from services.account_service import AccountService, RegisterService, TenantService
-from services.enterprise import rbac_service as enterprise_rbac_service
 from services.errors.account import AccountAlreadyInTenantError
 from services.feature_service import FeatureService
 
 
 class MemberInvitePayload(BaseModel):
     emails: list[str] = Field(default_factory=list)
-    role: str
+    role: TenantAccountRole
     language: str | None = None
 
 
@@ -71,18 +70,6 @@ register_schema_models(
 )
 
 
-def _serialize_member_roles(current_role: str | None, member_roles: list[enterprise_rbac_service.MemberRoleSummary]) -> list[dict[str, str]]:
-    if member_roles:
-        return [{"id": role.id, "name": role.name} for role in member_roles]
-    if current_role:
-        return [{"id": current_role, "name": current_role}]
-    return []
-
-
-def _normalize_enum_value(value: object) -> str:
-    normalized = getattr(value, "value", value)
-    return str(normalized) if normalized is not None else ""
-
 def _is_role_enabled(role: TenantAccountRole | str, tenant_id: str) -> bool:
     if role != TenantAccountRole.DATASET_OPERATOR:
         return True
@@ -102,36 +89,7 @@ class MemberListApi(Resource):
         if not current_user.current_tenant:
             raise ValueError("No current tenant")
         members = TenantService.get_tenant_members(current_user.current_tenant)
-        if dify_config.RBAC_ENABLED:
-            member_ids = [member.id for member in members]
-            member_roles = enterprise_rbac_service.RBACService.MemberRoles.batch_get(
-                str(current_user.current_tenant.id),
-                current_user.id,
-                member_ids,
-            )
-            roles_map = {item.account_id: item.roles for item in member_roles}
-        else:
-            roles_map = {}
-
-        serialized_members = []
-        for member in members:
-            current_role = _normalize_enum_value(member.current_role)
-            serialized_members.append(
-                {
-                    "id": member.id,
-                    "name": member.name,
-                    "email": member.email,
-                    "avatar": member.avatar,
-                    "last_login_at": member.last_login_at,
-                    "last_active_at": member.last_active_at,
-                    "created_at": member.created_at,
-                    "role": current_role,
-                    "roles": _serialize_member_roles(current_role, roles_map.get(member.id, [])),
-                    "status": _normalize_enum_value(member.status),
-                }
-            )
-
-        member_models = TypeAdapter(list[AccountWithRole]).validate_python(serialized_members)
+        member_models = TypeAdapter(list[AccountWithRole]).validate_python(members, from_attributes=True)
         response = AccountWithRoleList(accounts=member_models)
         return response.model_dump(mode="json"), 200
 
@@ -152,9 +110,8 @@ class MemberInviteEmailApi(Resource):
         invitee_emails = args.emails
         invitee_role = args.role
         interface_language = args.language
-        if not dify_config.RBAC_ENABLED:
-            if not TenantAccountRole.is_valid_role(invitee_role) or not TenantAccountRole.is_non_owner_role(invitee_role):
-                return {"code": "invalid-role", "message": "Invalid role"}, 400
+        if not TenantAccountRole.is_non_owner_role(invitee_role):
+            return {"code": "invalid-role", "message": "Invalid role"}, 400
         current_user, _ = current_account_with_tenant()
         inviter = current_user
         if not inviter.current_tenant:

api/controllers/console/workspace/plugin.py

@@ -1,15 +1,15 @@
 import io
 from collections.abc import Mapping
-from typing import Any, Literal, TypedDict
+from typing import Any, Literal
 
 from flask import request, send_file
 from flask_restx import Resource
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, Field
 from werkzeug.datastructures import FileStorage
 from werkzeug.exceptions import Forbidden
 
 from configs import dify_config
-from controllers.common.schema import query_params_from_model, register_enum_models, register_schema_models
+from controllers.common.schema import register_enum_models, register_schema_models
 from controllers.console import console_ns
 from controllers.console.workspace import plugin_permission_required
 from controllers.console.wraps import account_initialization_required, is_admin_or_owner_required, setup_required
@@ -23,14 +23,6 @@ from services.plugin.plugin_permission_service import PluginPermissionService
 from services.plugin.plugin_service import PluginService
 
 
-class AutoUpgradeSettingsResponse(TypedDict):
-    strategy_setting: TenantPluginAutoUpgradeStrategy.StrategySetting
-    upgrade_time_of_day: int
-    upgrade_mode: TenantPluginAutoUpgradeStrategy.UpgradeMode
-    exclude_plugins: list[str]
-    include_plugins: list[str]
-
-
 class ParserList(BaseModel):
     page: int = Field(default=1, ge=1, description="Page number")
     page_size: int = Field(default=256, ge=1, le=256, description="Page size (1-256)")
@@ -94,8 +86,8 @@ class ParserUninstall(BaseModel):
 
 
 class ParserPermissionChange(BaseModel):
-    install_permission: TenantPluginPermission.InstallPermission = TenantPluginPermission.InstallPermission.EVERYONE
-    debug_permission: TenantPluginPermission.DebugPermission = TenantPluginPermission.DebugPermission.EVERYONE
+    install_permission: TenantPluginPermission.InstallPermission
+    debug_permission: TenantPluginPermission.DebugPermission
 
 
 class ParserDynamicOptions(BaseModel):
@@ -131,22 +123,13 @@ class PluginAutoUpgradeSettingsPayload(BaseModel):
     include_plugins: list[str] = Field(default_factory=list)
 
 
-class ParserAutoUpgradeChange(BaseModel):
-    model_config = ConfigDict(extra="forbid")
-
-    category: TenantPluginAutoUpgradeStrategy.PluginCategory
+class ParserPreferencesChange(BaseModel):
+    permission: PluginPermissionSettingsPayload
     auto_upgrade: PluginAutoUpgradeSettingsPayload
 
 
-class ParserAutoUpgradeFetch(BaseModel):
-    category: TenantPluginAutoUpgradeStrategy.PluginCategory
-
-
 class ParserExcludePlugin(BaseModel):
-    model_config = ConfigDict(extra="forbid")
-
     plugin_id: str
-    category: TenantPluginAutoUpgradeStrategy.PluginCategory
 
 
 class ParserReadme(BaseModel):
@@ -173,8 +156,7 @@ register_schema_models(
     ParserPermissionChange,
     ParserDynamicOptions,
     ParserDynamicOptionsWithCredentials,
-    ParserAutoUpgradeChange,
-    ParserAutoUpgradeFetch,
+    ParserPreferencesChange,
     ParserExcludePlugin,
     ParserReadme,
 )
@@ -182,36 +164,12 @@ register_schema_models(
 register_enum_models(
     console_ns,
     TenantPluginPermission.DebugPermission,
-    TenantPluginAutoUpgradeStrategy.PluginCategory,
     TenantPluginAutoUpgradeStrategy.UpgradeMode,
     TenantPluginAutoUpgradeStrategy.StrategySetting,
     TenantPluginPermission.InstallPermission,
 )
 
 
-def _default_auto_upgrade_settings(
-    tenant_id: str,
-    category: TenantPluginAutoUpgradeStrategy.PluginCategory,
-) -> AutoUpgradeSettingsResponse:
-    return {
-        "strategy_setting": PluginAutoUpgradeService.default_strategy_setting_for_category(category),
-        "upgrade_time_of_day": PluginAutoUpgradeService.default_upgrade_time_of_day(tenant_id),
-        "upgrade_mode": TenantPluginAutoUpgradeStrategy.UpgradeMode.EXCLUDE,
-        "exclude_plugins": [],
-        "include_plugins": [],
-    }
-
-
-def _auto_upgrade_settings_to_dict(strategy: TenantPluginAutoUpgradeStrategy) -> AutoUpgradeSettingsResponse:
-    return {
-        "strategy_setting": strategy.strategy_setting,
-        "upgrade_time_of_day": strategy.upgrade_time_of_day,
-        "upgrade_mode": strategy.upgrade_mode,
-        "exclude_plugins": strategy.exclude_plugins,
-        "include_plugins": strategy.include_plugins,
-    }
-
-
 def _read_upload_content(file: FileStorage, max_size: int) -> bytes:
     """
     Read the uploaded file and validate its actual size before delegating to the plugin service.
@@ -659,13 +617,11 @@ class PluginChangePermissionApi(Resource):
 
         tenant_id = current_tenant_id
 
-        set_permission_result = PluginPermissionService.change_permission(
-            tenant_id, args.install_permission, args.debug_permission
-        )
-        if not set_permission_result:
-            return jsonable_encoder({"success": False, "message": "Failed to set permission"})
-
-        return jsonable_encoder({"success": True})
+        return {
+            "success": PluginPermissionService.change_permission(
+                tenant_id, args.install_permission, args.debug_permission
+            )
+        }
 
 
 @console_ns.route("/workspaces/current/plugin/permission/fetch")
@@ -754,9 +710,9 @@ class PluginFetchDynamicSelectOptionsWithCredentialsApi(Resource):
         return jsonable_encoder({"options": options})
 
 
-@console_ns.route("/workspaces/current/plugin/auto-upgrade/change")
-class PluginChangeAutoUpgradeApi(Resource):
-    @console_ns.expect(console_ns.models[ParserAutoUpgradeChange.__name__])
+@console_ns.route("/workspaces/current/plugin/preferences/change")
+class PluginChangePreferencesApi(Resource):
+    @console_ns.expect(console_ns.models[ParserPreferencesChange.__name__])
     @setup_required
     @login_required
     @account_initialization_required
@@ -765,17 +721,38 @@ class PluginChangeAutoUpgradeApi(Resource):
         if not user.is_admin_or_owner:
             raise Forbidden()
 
-        args = ParserAutoUpgradeChange.model_validate(console_ns.payload)
+        args = ParserPreferencesChange.model_validate(console_ns.payload)
+
+        permission = args.permission
+
+        install_permission = permission.install_permission
+        debug_permission = permission.debug_permission
 
         auto_upgrade = args.auto_upgrade
+
+        strategy_setting = auto_upgrade.strategy_setting
+        upgrade_time_of_day = auto_upgrade.upgrade_time_of_day
+        upgrade_mode = auto_upgrade.upgrade_mode
+        exclude_plugins = auto_upgrade.exclude_plugins
+        include_plugins = auto_upgrade.include_plugins
+
+        # set permission
+        set_permission_result = PluginPermissionService.change_permission(
+            tenant_id,
+            install_permission,
+            debug_permission,
+        )
+        if not set_permission_result:
+            return jsonable_encoder({"success": False, "message": "Failed to set permission"})
+
+        # set auto upgrade strategy
         set_auto_upgrade_strategy_result = PluginAutoUpgradeService.change_strategy(
             tenant_id,
-            auto_upgrade.strategy_setting,
-            auto_upgrade.upgrade_time_of_day,
-            auto_upgrade.upgrade_mode,
-            auto_upgrade.exclude_plugins,
-            auto_upgrade.include_plugins,
-            category=args.category,
+            strategy_setting,
+            upgrade_time_of_day,
+            upgrade_mode,
+            exclude_plugins,
+            include_plugins,
         )
         if not set_auto_upgrade_strategy_result:
             return jsonable_encoder({"success": False, "message": "Failed to set auto upgrade strategy"})
@@ -783,32 +760,46 @@ class PluginChangeAutoUpgradeApi(Resource):
         return jsonable_encoder({"success": True})
 
 
-@console_ns.route("/workspaces/current/plugin/auto-upgrade/fetch")
-class PluginFetchAutoUpgradeApi(Resource):
-    @console_ns.doc(params=query_params_from_model(ParserAutoUpgradeFetch))
+@console_ns.route("/workspaces/current/plugin/preferences/fetch")
+class PluginFetchPreferencesApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
     def get(self):
         _, tenant_id = current_account_with_tenant()
 
-        args = ParserAutoUpgradeFetch.model_validate(request.args.to_dict(flat=True))
-        auto_upgrade = PluginAutoUpgradeService.get_strategy(tenant_id, args.category)
-        auto_upgrade_dict = (
-            _auto_upgrade_settings_to_dict(auto_upgrade)
-            if auto_upgrade
-            else _default_auto_upgrade_settings(tenant_id, args.category)
-        )
+        permission = PluginPermissionService.get_permission(tenant_id)
+        permission_dict = {
+            "install_permission": TenantPluginPermission.InstallPermission.EVERYONE,
+            "debug_permission": TenantPluginPermission.DebugPermission.EVERYONE,
+        }
 
-        return jsonable_encoder(
-            {
-                "category": args.category,
-                "auto_upgrade": auto_upgrade_dict,
+        if permission:
+            permission_dict["install_permission"] = permission.install_permission
+            permission_dict["debug_permission"] = permission.debug_permission
+
+        auto_upgrade = PluginAutoUpgradeService.get_strategy(tenant_id)
+        auto_upgrade_dict = {
+            "strategy_setting": TenantPluginAutoUpgradeStrategy.StrategySetting.DISABLED,
+            "upgrade_time_of_day": 0,
+            "upgrade_mode": TenantPluginAutoUpgradeStrategy.UpgradeMode.EXCLUDE,
+            "exclude_plugins": [],
+            "include_plugins": [],
+        }
+
+        if auto_upgrade:
+            auto_upgrade_dict = {
+                "strategy_setting": auto_upgrade.strategy_setting,
+                "upgrade_time_of_day": auto_upgrade.upgrade_time_of_day,
+                "upgrade_mode": auto_upgrade.upgrade_mode,
+                "exclude_plugins": auto_upgrade.exclude_plugins,
+                "include_plugins": auto_upgrade.include_plugins,
             }
-        )
+
+        return jsonable_encoder({"permission": permission_dict, "auto_upgrade": auto_upgrade_dict})
 
 
-@console_ns.route("/workspaces/current/plugin/auto-upgrade/exclude")
+@console_ns.route("/workspaces/current/plugin/preferences/autoupgrade/exclude")
 class PluginAutoUpgradeExcludePluginApi(Resource):
     @console_ns.expect(console_ns.models[ParserExcludePlugin.__name__])
     @setup_required
@@ -820,9 +811,7 @@ class PluginAutoUpgradeExcludePluginApi(Resource):
 
         args = ParserExcludePlugin.model_validate(console_ns.payload)
 
-        return jsonable_encoder(
-            {"success": PluginAutoUpgradeService.exclude_plugin(tenant_id, args.plugin_id, args.category)}
-        )
+        return jsonable_encoder({"success": PluginAutoUpgradeService.exclude_plugin(tenant_id, args.plugin_id)})
 
 
 @console_ns.route("/workspaces/current/plugin/readme")

api/controllers/console/workspace/rbac.py

@@ -1,614 +0,0 @@
-from __future__ import annotations
-
-from collections.abc import Callable
-from functools import wraps
-from typing import Any
-
-from flask import request
-from flask_restx import Resource
-from pydantic import AliasChoices, BaseModel, ConfigDict, Field, ValidationError, field_validator
-from werkzeug.exceptions import Forbidden, NotFound
-
-from configs import dify_config
-from controllers.console import console_ns
-from libs.login import current_account_with_tenant, login_required
-from services.enterprise import rbac_service as svc
-
-
-_LEGACY_ROLE_PERMISSION_KEYS: dict[str, list[str]] = {
-    # This is a compatibility projection from the pre-RBAC workspace roles into
-    # the 2.0 permission matrix documented in "权限整理2.0". It intentionally
-    # models the product-facing role surface for the new RBAC UI instead of the
-    # legacy backend's exact hard-authorization checks.
-    "owner": [
-        *svc._LEGACY_WORKSPACE_OWNER_KEYS,
-        *svc._LEGACY_APP_OWNER_KEYS,
-        *svc._LEGACY_DATASET_OWNER_KEYS,
-    ],
-    "admin": [
-        *svc._LEGACY_WORKSPACE_ADMIN_KEYS,
-        *svc._LEGACY_APP_ADMIN_KEYS,
-        *svc._LEGACY_DATASET_ADMIN_KEYS,
-    ],
-    "editor": [
-        *svc._LEGACY_WORKSPACE_EDITOR_KEYS,
-        *svc._LEGACY_APP_EDITOR_KEYS,
-        *svc._LEGACY_DATASET_EDITOR_KEYS,
-    ],
-    "normal": [
-        *svc._LEGACY_WORKSPACE_NORMAL_KEYS,
-        *svc._LEGACY_APP_NORMAL_KEYS,
-    ],
-    "dataset_operator": [
-        *svc._LEGACY_WORKSPACE_DATASET_OPERATOR_KEYS,
-        *svc._LEGACY_DATASET_DATASET_OPERATOR_KEYS,
-    ],
-}
-
-
-def _current_ids() -> tuple[str, str]:
-    """Return ``(tenant_id, account_id)`` for the authenticated user, or
-    raise a 404 when no tenant is associated with the session.
-    """
-
-    user, tenant_id = current_account_with_tenant()
-    if not tenant_id:
-        raise NotFound("Current workspace not found")
-    return tenant_id, user.id
-
-
-def _payload(model: type[BaseModel]) -> Any:
-    """Validate the JSON body against ``model`` or raise ``ValidationError``.
-
-    ``ValidationError`` bubbles up as HTTP 400 thanks to
-    ``controllers/common/helpers.py`` error handling.
-    """
-    try:
-        return model.model_validate(console_ns.payload or {})
-    except ValidationError as exc:
-        # Re-raise as-is so the upstream error handler renders a 400.
-        raise exc
-
-
-def _dump(model: BaseModel) -> dict[str, Any]:
-    return model.model_dump(mode="json")
-
-
-class _PaginationQuery(BaseModel):
-    model_config = ConfigDict(extra="ignore")
-
-    page_number: int | None = Field(default=None, ge=1, validation_alias=AliasChoices("page", "page_number"))
-    results_per_page: int | None = Field(
-        default=None, ge=1, le=100, validation_alias=AliasChoices("limit", "results_per_page")
-    )
-    reverse: bool | None = None
-
-    def to_inner_options(self) -> svc.ListOption:
-        return svc.ListOption.model_validate(self.model_dump())
-
-
-class _RolesListQuery(_PaginationQuery):
-    include_owner: int = Field(default=0, ge=0, le=1)
-
-
-def _pagination_options() -> svc.ListOption:
-    return _PaginationQuery.model_validate(request.args.to_dict(flat=True)).to_inner_options()
-
-
-def _filter_out_owner(paginated: svc.Paginated[svc.RBACRole]) -> svc.Paginated[svc.RBACRole]:
-    filtered = [r for r in paginated.data if r.name not in {"所有者", "owner"}]
-    return svc.Paginated[svc.RBACRole](
-        data=filtered,
-        pagination=paginated.pagination,
-    )
-
-
-def _legacy_workspace_roles(options: svc.ListOption | None = None) -> svc.Paginated[svc.RBACRole]:
-    """Return the built-in legacy workspace roles in the RBAC list shape.
-
-    This keeps the new `/rbac/roles` endpoint compatible with the original
-    Dify role model when enterprise RBAC is disabled.
-    """
-
-    legacy_roles = [
-        svc.RBACRole(
-            id=role_name,
-            tenant_id="",
-            type=svc.RBACRoleType.WORKSPACE.value,
-            category="global_system_default",
-            name=role_name,
-            description="",
-            is_builtin=True,
-            permission_keys=list(_LEGACY_ROLE_PERMISSION_KEYS[role_name]),
-            role_tag="owner" if role_name == "owner" else "",
-        )
-        for role_name in ("owner", "admin", "editor", "normal", "dataset_operator")
-    ]
-
-    page_number = options.page_number if options and options.page_number is not None else 1
-    results_per_page = options.results_per_page if options and options.results_per_page is not None else len(legacy_roles)
-    reverse = options.reverse if options and options.reverse is not None else False
-
-    ordered_roles = list(reversed(legacy_roles)) if reverse else legacy_roles
-    start = max(page_number - 1, 0) * results_per_page
-    end = start + results_per_page
-    paged_roles = ordered_roles[start:end]
-    total_count = len(legacy_roles)
-    total_pages = (total_count + results_per_page - 1) // results_per_page if results_per_page > 0 else 0
-
-    return svc.Paginated[svc.RBACRole](
-        data=paged_roles,
-        pagination=svc.Pagination(
-            total_count=total_count,
-            per_page=results_per_page,
-            current_page=page_number,
-            total_pages=total_pages,
-        ),
-    )
-
-
-# ---------------------------------------------------------------------------
-# Permission catalogs.
-# ---------------------------------------------------------------------------
-
-
-@console_ns.route("/workspaces/current/rbac/role-permissions/catalog")
-class RBACWorkspaceCatalogApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.Catalog.workspace(tenant_id, account_id))
-
-
-@console_ns.route("/workspaces/current/rbac/role-permissions/catalog/app")
-class RBACAppCatalogApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.Catalog.app(tenant_id, account_id))
-
-
-@console_ns.route("/workspaces/current/rbac/role-permissions/catalog/dataset")
-class RBACDatasetCatalogApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.Catalog.dataset(tenant_id, account_id))
-
-
-# ---------------------------------------------------------------------------
-# Roles.
-# ---------------------------------------------------------------------------
-
-
-class _RoleUpsertRequest(BaseModel):
-    """Accepts the payload sent by the Create/Edit Role dialog."""
-
-    name: str
-    description: str = ""
-    permission_keys: list[str] = []
-
-    def to_mutation(self) -> svc.RoleMutation:
-        return svc.RoleMutation(
-            name=self.name,
-            description=self.description,
-            permission_keys=list(self.permission_keys),
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/roles")
-class RBACRolesApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        query = _RolesListQuery.model_validate(request.args.to_dict(flat=True))
-        options = query.to_inner_options()
-        if not dify_config.RBAC_ENABLED:
-            result = _legacy_workspace_roles(options)
-        else:
-            result = svc.RBACService.Roles.list(tenant_id, account_id, options=options)
-        if query.include_owner == 0:
-            result = _filter_out_owner(result)
-
-        data = []
-        for role in result.data:
-            if role.name in {"所有者", "owner"}:
-                role.role_tag = "owner"
-            else:
-                role.role_tag = ""
-            data.append(role)
-        result.data = data
-        return _dump(result)
-
-    @login_required
-    def post(self):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_RoleUpsertRequest)
-        role = svc.RBACService.Roles.create(tenant_id, account_id, request.to_mutation())
-        return _dump(role), 201
-
-
-@console_ns.route("/workspaces/current/rbac/roles/<uuid:role_id>")
-class RBACRoleItemApi(Resource):
-    @login_required
-    def get(self, role_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.Roles.get(tenant_id, account_id, str(role_id)))
-
-    @login_required
-    def put(self, role_id):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_RoleUpsertRequest)
-        role = svc.RBACService.Roles.update(tenant_id, account_id, str(role_id), request.to_mutation())
-        return _dump(role)
-
-    @login_required
-    def delete(self, role_id):
-        tenant_id, account_id = _current_ids()
-        svc.RBACService.Roles.delete(tenant_id, account_id, str(role_id))
-        return {"result": "success"}
-
-
-@console_ns.route("/workspaces/current/rbac/roles/<uuid:role_id>/copy")
-class RBACRoleCopyApi(Resource):
-    @login_required
-    def post(self, role_id):
-        tenant_id, account_id = _current_ids()
-        role = svc.RBACService.Roles.copy(tenant_id, account_id, str(role_id))
-        return _dump(role), 201
-
-
-# ---------------------------------------------------------------------------
-# Access policies (tenant-level permission sets).
-# ---------------------------------------------------------------------------
-
-
-class _AccessPolicyCreateRequest(BaseModel):
-    name: str
-    resource_type: svc.RBACResourceType
-    description: str = ""
-    permission_keys: list[str] = []
-
-
-class _AccessPolicyUpdateRequest(BaseModel):
-    name: str
-    description: str = ""
-    permission_keys: list[str] = []
-
-
-@console_ns.route("/workspaces/current/rbac/access-policies")
-class RBACAccessPoliciesApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        # `resource_type` is exposed as a query argument so the UI can show
-        # only app-scoped or only dataset-scoped permission sets.
-        resource_type = request.args.get("resource_type") or None
-        return _dump(
-            svc.RBACService.AccessPolicies.list(
-                tenant_id,
-                account_id,
-                resource_type=resource_type,
-                options=_pagination_options(),
-            )
-        )
-
-    @login_required
-    def post(self):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_AccessPolicyCreateRequest)
-        policy = svc.RBACService.AccessPolicies.create(
-            tenant_id,
-            account_id,
-            svc.AccessPolicyCreate(
-                name=request.name,
-                resource_type=request.resource_type,
-                description=request.description,
-                permission_keys=list(request.permission_keys),
-            ),
-        )
-        return _dump(policy), 201
-
-
-@console_ns.route("/workspaces/current/rbac/access-policies/<uuid:policy_id>")
-class RBACAccessPolicyItemApi(Resource):
-    @login_required
-    def get(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.AccessPolicies.get(tenant_id, account_id, str(policy_id)))
-
-    @login_required
-    def put(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_AccessPolicyUpdateRequest)
-        policy = svc.RBACService.AccessPolicies.update(
-            tenant_id,
-            account_id,
-            str(policy_id),
-            svc.AccessPolicyUpdate(
-                name=request.name,
-                description=request.description,
-                permission_keys=list(request.permission_keys),
-            ),
-        )
-        return _dump(policy)
-
-    @login_required
-    def delete(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        svc.RBACService.AccessPolicies.delete(tenant_id, account_id, str(policy_id))
-        return {"result": "success"}
-
-
-@console_ns.route("/workspaces/current/rbac/access-policies/<uuid:policy_id>/copy")
-class RBACAccessPolicyCopyApi(Resource):
-    @login_required
-    def post(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        policy = svc.RBACService.AccessPolicies.copy(tenant_id, account_id, str(policy_id))
-        return _dump(policy), 201
-
-
-# ---------------------------------------------------------------------------
-# Per-app access (App Access Config).
-# ---------------------------------------------------------------------------
-
-
-class _ReplaceBindingsRequest(BaseModel):
-    role_ids: list[str] = []
-    account_ids: list[str] = []
-
-    @field_validator("role_ids", "account_ids", mode="before")
-    @classmethod
-    def _coerce_bindings(cls, value: Any) -> list[str]:
-        if value is None:
-            return []
-        return value
-
-
-@console_ns.route("/workspaces/current/rbac/my-permissions")
-class RBACMyPermissionsApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.MyPermissions.get(
-                tenant_id,
-                account_id,
-                app_id=request.args.get("app_id") or None,
-                dataset_id=request.args.get("dataset_id") or None,
-            )
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/apps/<uuid:app_id>/access-policy")
-class RBACAppMatrixApi(Resource):
-    @login_required
-    def get(self, app_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.AppAccess.matrix(tenant_id, account_id, str(app_id)))
-
-
-@console_ns.route("/workspaces/current/rbac/apps/<uuid:app_id>/access-policies/<uuid:policy_id>/role-bindings")
-class RBACAppRoleBindingsApi(Resource):
-    @login_required
-    def get(self, app_id, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.AppAccess.list_role_bindings(tenant_id, account_id, str(app_id), str(policy_id))
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/apps/<uuid:app_id>/access-policies/<uuid:policy_id>/member-bindings")
-class RBACAppMemberBindingsApi(Resource):
-    @login_required
-    def get(self, app_id, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.AppAccess.list_member_bindings(tenant_id, account_id, str(app_id), str(policy_id))
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/apps/<uuid:app_id>/access-policies/<uuid:policy_id>/bindings")
-class RBACAppBindingsApi(Resource):
-    @login_required
-    def put(self, app_id, policy_id):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_ReplaceBindingsRequest)
-        return _dump(
-            svc.RBACService.AppAccess.replace_bindings(
-                tenant_id,
-                account_id,
-                str(app_id),
-                str(policy_id),
-                svc.ReplaceBindings(role_ids=list(request.role_ids), account_ids=list(request.account_ids)),
-            )
-        )
-
-
-# ---------------------------------------------------------------------------
-# Per-dataset access (Knowledge Base Access Config).
-# ---------------------------------------------------------------------------
-
-
-@console_ns.route("/workspaces/current/rbac/datasets/<uuid:dataset_id>/access-policy")
-class RBACDatasetMatrixApi(Resource):
-    @login_required
-    def get(self, dataset_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.DatasetAccess.matrix(tenant_id, account_id, str(dataset_id)))
-
-
-@console_ns.route("/workspaces/current/rbac/datasets/<uuid:dataset_id>/access-policies/<uuid:policy_id>/role-bindings")
-class RBACDatasetRoleBindingsApi(Resource):
-    @login_required
-    def get(self, dataset_id, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.DatasetAccess.list_role_bindings(
-                tenant_id, account_id, str(dataset_id), str(policy_id)
-            )
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/datasets/<uuid:dataset_id>/access-policies/<uuid:policy_id>/bindings")
-class RBACDatasetBindingsApi(Resource):
-    @login_required
-    def put(self, dataset_id, policy_id):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_ReplaceBindingsRequest)
-        return _dump(
-            svc.RBACService.DatasetAccess.replace_bindings(
-                tenant_id,
-                account_id,
-                str(dataset_id),
-                str(policy_id),
-                svc.ReplaceBindings(role_ids=list(request.role_ids), account_ids=list(request.account_ids)),
-            )
-        )
-
-
-@console_ns.route(
-    "/workspaces/current/rbac/datasets/<uuid:dataset_id>/access-policies/<uuid:policy_id>/member-bindings"
-)
-class RBACDatasetMemberBindingsApi(Resource):
-    @login_required
-    def get(self, dataset_id, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.DatasetAccess.list_member_bindings(
-                tenant_id, account_id, str(dataset_id), str(policy_id)
-            )
-        )
-
-
-# ---------------------------------------------------------------------------
-# Workspace-level access (Settings > Access Rules).
-# ---------------------------------------------------------------------------
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/apps/access-policy")
-class RBACWorkspaceAppMatrixApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        options = _pagination_options()
-        return _dump(svc.RBACService.WorkspaceAccess.app_matrix(tenant_id, account_id, options=options))
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/apps/access-policies/<uuid:policy_id>/role-bindings")
-class RBACWorkspaceAppRoleBindingsApi(Resource):
-    @login_required
-    def get(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.WorkspaceAccess.list_app_role_bindings(tenant_id, account_id, str(policy_id))
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/apps/access-policies/<uuid:policy_id>/bindings")
-class RBACWorkspaceAppBindingsApi(Resource):
-    @login_required
-    def put(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_ReplaceBindingsRequest)
-        return _dump(
-            svc.RBACService.WorkspaceAccess.replace_app_bindings(
-                tenant_id,
-                account_id,
-                str(policy_id),
-                svc.ReplaceBindings(role_ids=list(request.role_ids), account_ids=list(request.account_ids)),
-            )
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/apps/access-policies/<uuid:policy_id>/member-bindings")
-class RBACWorkspaceAppMemberBindingsApi(Resource):
-    @login_required
-    def get(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.WorkspaceAccess.list_app_member_bindings(tenant_id, account_id, str(policy_id))
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/datasets/access-policy")
-class RBACWorkspaceDatasetMatrixApi(Resource):
-    @login_required
-    def get(self):
-        tenant_id, account_id = _current_ids()
-        options = _pagination_options()
-        return _dump(svc.RBACService.WorkspaceAccess.dataset_matrix(tenant_id, account_id, options=options))
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/datasets/access-policies/<uuid:policy_id>/role-bindings")
-class RBACWorkspaceDatasetRoleBindingsApi(Resource):
-    @login_required
-    def get(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.WorkspaceAccess.list_dataset_role_bindings(tenant_id, account_id, str(policy_id))
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/datasets/access-policies/<uuid:policy_id>/bindings")
-class RBACWorkspaceDatasetBindingsApi(Resource):
-    @login_required
-    def put(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_ReplaceBindingsRequest)
-        return _dump(
-            svc.RBACService.WorkspaceAccess.replace_dataset_bindings(
-                tenant_id,
-                account_id,
-                str(policy_id),
-                svc.ReplaceBindings(role_ids=list(request.role_ids), account_ids=list(request.account_ids)),
-            )
-        )
-
-
-@console_ns.route("/workspaces/current/rbac/workspace/datasets/access-policies/<uuid:policy_id>/member-bindings")
-class RBACWorkspaceDatasetMemberBindingsApi(Resource):
-    @login_required
-    def get(self, policy_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(
-            svc.RBACService.WorkspaceAccess.list_dataset_member_bindings(tenant_id, account_id, str(policy_id))
-        )
-
-
-# ---------------------------------------------------------------------------
-# Member ↔ role bindings (Settings > Members > Assign roles).
-# ---------------------------------------------------------------------------
-
-
-class _ReplaceMemberRolesRequest(BaseModel):
-    role_ids: list[str] = []
-
-    @field_validator("role_ids", mode="before")
-    @classmethod
-    def _coerce_role_ids(cls, value: Any) -> list[str]:
-        if value is None:
-            return []
-        return value
-
-
-@console_ns.route("/workspaces/current/rbac/members/<uuid:member_id>/rbac-roles")
-class RBACMemberRolesApi(Resource):
-    @login_required
-    def get(self, member_id):
-        tenant_id, account_id = _current_ids()
-        return _dump(svc.RBACService.MemberRoles.get(tenant_id, account_id, str(member_id)))
-
-    @login_required
-    def put(self, member_id):
-        tenant_id, account_id = _current_ids()
-        request = _payload(_ReplaceMemberRolesRequest)
-        return _dump(
-            svc.RBACService.MemberRoles.replace(
-                tenant_id,
-                account_id,
-                str(member_id),
-                role_ids=list(request.role_ids),
-            )
-        )

api/controllers/console/workspace/snippets.py

@@ -1,380 +0,0 @@
-import logging
-from urllib.parse import quote
-
-from flask import Response, request
-from flask_restx import Resource, marshal
-from sqlalchemy.orm import Session
-from werkzeug.exceptions import NotFound
-
-from controllers.common.schema import register_schema_models
-from controllers.console import console_ns
-from controllers.console.snippets.payloads import (
-    CreateSnippetPayload,
-    IncludeSecretQuery,
-    SnippetImportPayload,
-    SnippetListQuery,
-    UpdateSnippetPayload,
-)
-from controllers.console.wraps import (
-    account_initialization_required,
-    edit_permission_required,
-    setup_required,
-)
-from extensions.ext_database import db
-from fields.snippet_fields import snippet_fields, snippet_list_fields, snippet_pagination_fields
-from libs.login import current_account_with_tenant, login_required
-from models.snippet import SnippetType
-from services.app_dsl_service import ImportStatus
-from services.snippet_dsl_service import SnippetDslService
-from services.snippet_service import SnippetService
-
-logger = logging.getLogger(__name__)
-
-# Register Pydantic models with Swagger
-register_schema_models(
-    console_ns,
-    SnippetListQuery,
-    CreateSnippetPayload,
-    UpdateSnippetPayload,
-    SnippetImportPayload,
-    IncludeSecretQuery,
-)
-
-# Create namespace models for marshaling
-snippet_model = console_ns.model("Snippet", snippet_fields)
-snippet_list_model = console_ns.model("SnippetList", snippet_list_fields)
-snippet_pagination_model = console_ns.model("SnippetPagination", snippet_pagination_fields)
-
-
-@console_ns.route("/workspaces/current/customized-snippets")
-class CustomizedSnippetsApi(Resource):
-    @console_ns.doc("list_customized_snippets")
-    @console_ns.expect(console_ns.models.get(SnippetListQuery.__name__))
-    @console_ns.response(200, "Snippets retrieved successfully", snippet_pagination_model)
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self):
-        """List customized snippets with pagination and search."""
-        _, current_tenant_id = current_account_with_tenant()
-
-        query_params = request.args.to_dict()
-        query = SnippetListQuery.model_validate(query_params)
-
-        snippets, total, has_more = SnippetService.get_snippets(
-            tenant_id=current_tenant_id,
-            page=query.page,
-            limit=query.limit,
-            keyword=query.keyword,
-            is_published=query.is_published,
-            creators=query.creators,
-        )
-
-        return {
-            "data": marshal(snippets, snippet_list_fields),
-            "page": query.page,
-            "limit": query.limit,
-            "total": total,
-            "has_more": has_more,
-        }, 200
-
-    @console_ns.doc("create_customized_snippet")
-    @console_ns.expect(console_ns.models.get(CreateSnippetPayload.__name__))
-    @console_ns.response(201, "Snippet created successfully", snippet_model)
-    @console_ns.response(400, "Invalid request or name already exists")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def post(self):
-        """Create a new customized snippet."""
-        current_user, current_tenant_id = current_account_with_tenant()
-
-        payload = CreateSnippetPayload.model_validate(console_ns.payload or {})
-
-        try:
-            snippet_type = SnippetType(payload.type)
-        except ValueError:
-            snippet_type = SnippetType.NODE
-
-        try:
-            snippet = SnippetService.create_snippet(
-                tenant_id=current_tenant_id,
-                name=payload.name,
-                description=payload.description,
-                snippet_type=snippet_type,
-                icon_info=payload.icon_info.model_dump() if payload.icon_info else None,
-                input_fields=[f.model_dump() for f in payload.input_fields] if payload.input_fields else None,
-                account=current_user,
-            )
-        except ValueError as e:
-            return {"message": str(e)}, 400
-
-        return marshal(snippet, snippet_fields), 201
-
-
-@console_ns.route("/workspaces/current/customized-snippets/<uuid:snippet_id>")
-class CustomizedSnippetDetailApi(Resource):
-    @console_ns.doc("get_customized_snippet")
-    @console_ns.response(200, "Snippet retrieved successfully", snippet_model)
-    @console_ns.response(404, "Snippet not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    def get(self, snippet_id: str):
-        """Get customized snippet details."""
-        _, current_tenant_id = current_account_with_tenant()
-
-        snippet = SnippetService.get_snippet_by_id(
-            snippet_id=str(snippet_id),
-            tenant_id=current_tenant_id,
-        )
-
-        if not snippet:
-            raise NotFound("Snippet not found")
-
-        return marshal(snippet, snippet_fields), 200
-
-    @console_ns.doc("update_customized_snippet")
-    @console_ns.expect(console_ns.models.get(UpdateSnippetPayload.__name__))
-    @console_ns.response(200, "Snippet updated successfully", snippet_model)
-    @console_ns.response(400, "Invalid request or name already exists")
-    @console_ns.response(404, "Snippet not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def patch(self, snippet_id: str):
-        """Update customized snippet."""
-        current_user, current_tenant_id = current_account_with_tenant()
-
-        snippet = SnippetService.get_snippet_by_id(
-            snippet_id=str(snippet_id),
-            tenant_id=current_tenant_id,
-        )
-
-        if not snippet:
-            raise NotFound("Snippet not found")
-
-        payload = UpdateSnippetPayload.model_validate(console_ns.payload or {})
-        update_data = payload.model_dump(exclude_unset=True)
-
-        if "icon_info" in update_data and update_data["icon_info"] is not None:
-            update_data["icon_info"] = payload.icon_info.model_dump() if payload.icon_info else None
-
-        if not update_data:
-            return {"message": "No valid fields to update"}, 400
-
-        try:
-            with Session(db.engine, expire_on_commit=False) as session:
-                snippet = session.merge(snippet)
-                snippet = SnippetService.update_snippet(
-                    session=session,
-                    snippet=snippet,
-                    account_id=current_user.id,
-                    data=update_data,
-                )
-                session.commit()
-        except ValueError as e:
-            return {"message": str(e)}, 400
-
-        return marshal(snippet, snippet_fields), 200
-
-    @console_ns.doc("delete_customized_snippet")
-    @console_ns.response(204, "Snippet deleted successfully")
-    @console_ns.response(404, "Snippet not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def delete(self, snippet_id: str):
-        """Delete customized snippet."""
-        _, current_tenant_id = current_account_with_tenant()
-
-        snippet = SnippetService.get_snippet_by_id(
-            snippet_id=str(snippet_id),
-            tenant_id=current_tenant_id,
-        )
-
-        if not snippet:
-            raise NotFound("Snippet not found")
-
-        with Session(db.engine) as session:
-            snippet = session.merge(snippet)
-            SnippetService.delete_snippet(
-                session=session,
-                snippet=snippet,
-            )
-            session.commit()
-
-        return "", 204
-
-
-@console_ns.route("/workspaces/current/customized-snippets/<uuid:snippet_id>/export")
-class CustomizedSnippetExportApi(Resource):
-    @console_ns.doc("export_customized_snippet")
-    @console_ns.doc(description="Export snippet configuration as DSL")
-    @console_ns.doc(params={"snippet_id": "Snippet ID to export"})
-    @console_ns.response(200, "Snippet exported successfully")
-    @console_ns.response(404, "Snippet not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def get(self, snippet_id: str):
-        """Export snippet as DSL."""
-        _, current_tenant_id = current_account_with_tenant()
-
-        snippet = SnippetService.get_snippet_by_id(
-            snippet_id=str(snippet_id),
-            tenant_id=current_tenant_id,
-        )
-
-        if not snippet:
-            raise NotFound("Snippet not found")
-
-        # Get include_secret parameter
-        query = IncludeSecretQuery.model_validate(request.args.to_dict())
-
-        with Session(db.engine) as session:
-            export_service = SnippetDslService(session)
-            result = export_service.export_snippet_dsl(snippet=snippet, include_secret=query.include_secret == "true")
-
-        # Set filename with .snippet extension
-        filename = f"{snippet.name}.snippet"
-        encoded_filename = quote(filename)
-        
-        response = Response(
-            result,
-            mimetype="application/x-yaml",
-        )
-        response.headers["Content-Disposition"] = f"attachment; filename*=UTF-8''{encoded_filename}"
-        response.headers["Content-Type"] = "application/x-yaml"
-        
-        return response
-
-
-@console_ns.route("/workspaces/current/customized-snippets/imports")
-class CustomizedSnippetImportApi(Resource):
-    @console_ns.doc("import_customized_snippet")
-    @console_ns.doc(description="Import snippet from DSL")
-    @console_ns.expect(console_ns.models.get(SnippetImportPayload.__name__))
-    @console_ns.response(200, "Snippet imported successfully")
-    @console_ns.response(202, "Import pending confirmation")
-    @console_ns.response(400, "Import failed")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def post(self):
-        """Import snippet from DSL."""
-        current_user, _ = current_account_with_tenant()
-        payload = SnippetImportPayload.model_validate(console_ns.payload or {})
-
-        with Session(db.engine) as session:
-            import_service = SnippetDslService(session)
-            result = import_service.import_snippet(
-                account=current_user,
-                import_mode=payload.mode,
-                yaml_content=payload.yaml_content,
-                yaml_url=payload.yaml_url,
-                snippet_id=payload.snippet_id,
-                name=payload.name,
-                description=payload.description,
-            )
-            session.commit()
-
-        # Return appropriate status code based on result
-        status = result.status
-        if status == ImportStatus.FAILED:
-            return result.model_dump(mode="json"), 400
-        elif status == ImportStatus.PENDING:
-            return result.model_dump(mode="json"), 202
-        return result.model_dump(mode="json"), 200
-
-
-@console_ns.route("/workspaces/current/customized-snippets/imports/<string:import_id>/confirm")
-class CustomizedSnippetImportConfirmApi(Resource):
-    @console_ns.doc("confirm_snippet_import")
-    @console_ns.doc(description="Confirm a pending snippet import")
-    @console_ns.doc(params={"import_id": "Import ID to confirm"})
-    @console_ns.response(200, "Import confirmed successfully")
-    @console_ns.response(400, "Import failed")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def post(self, import_id: str):
-        """Confirm a pending snippet import."""
-        current_user, _ = current_account_with_tenant()
-
-        with Session(db.engine) as session:
-            import_service = SnippetDslService(session)
-            result = import_service.confirm_import(import_id=import_id, account=current_user)
-            session.commit()
-
-        if result.status == ImportStatus.FAILED:
-            return result.model_dump(mode="json"), 400
-        return result.model_dump(mode="json"), 200
-
-
-@console_ns.route("/workspaces/current/customized-snippets/<uuid:snippet_id>/check-dependencies")
-class CustomizedSnippetCheckDependenciesApi(Resource):
-    @console_ns.doc("check_snippet_dependencies")
-    @console_ns.doc(description="Check dependencies for a snippet")
-    @console_ns.doc(params={"snippet_id": "Snippet ID"})
-    @console_ns.response(200, "Dependencies checked successfully")
-    @console_ns.response(404, "Snippet not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def get(self, snippet_id: str):
-        """Check dependencies for a snippet."""
-        _, current_tenant_id = current_account_with_tenant()
-
-        snippet = SnippetService.get_snippet_by_id(
-            snippet_id=str(snippet_id),
-            tenant_id=current_tenant_id,
-        )
-
-        if not snippet:
-            raise NotFound("Snippet not found")
-
-        with Session(db.engine) as session:
-            import_service = SnippetDslService(session)
-            result = import_service.check_dependencies(snippet=snippet)
-
-        return result.model_dump(mode="json"), 200
-
-
-@console_ns.route("/workspaces/current/customized-snippets/<uuid:snippet_id>/use-count/increment")
-class CustomizedSnippetUseCountIncrementApi(Resource):
-    @console_ns.doc("increment_snippet_use_count")
-    @console_ns.doc(description="Increment snippet use count by 1")
-    @console_ns.doc(params={"snippet_id": "Snippet ID"})
-    @console_ns.response(200, "Use count incremented successfully")
-    @console_ns.response(404, "Snippet not found")
-    @setup_required
-    @login_required
-    @account_initialization_required
-    @edit_permission_required
-    def post(self, snippet_id: str):
-        """Increment snippet use count when it is inserted into a workflow."""
-        _, current_tenant_id = current_account_with_tenant()
-
-        snippet = SnippetService.get_snippet_by_id(
-            snippet_id=str(snippet_id),
-            tenant_id=current_tenant_id,
-        )
-
-        if not snippet:
-            raise NotFound("Snippet not found")
-
-        with Session(db.engine) as session:
-            snippet = session.merge(snippet)
-            SnippetService.increment_use_count(session=session, snippet=snippet)
-            session.commit()
-            session.refresh(snippet)
-
-        return {"result": "success", "use_count": snippet.use_count}, 200

api/controllers/console/workspace/workspace.py

@@ -29,7 +29,7 @@ from controllers.console.wraps import (
 from enums.cloud_plan import CloudPlan
 from extensions.ext_database import db
 from fields.base import ResponseModel
-from libs.helper import TimestampField
+from libs.helper import TimestampField, to_timestamp
 from libs.login import current_account_with_tenant, login_required
 from models.account import Tenant, TenantCustomConfigDict, TenantStatus
 from services.account_service import TenantService
@@ -86,9 +86,7 @@ class TenantInfoResponse(ResponseModel):
     @field_validator("created_at", mode="before")
     @classmethod
     def _normalize_created_at(cls, value: datetime | int | None):
-        if isinstance(value, datetime):
-            return int(value.timestamp())
-        return value
+        return to_timestamp(value)
 
 
 register_schema_models(

api/controllers/inner_api/plugin/wraps.py

@@ -20,10 +20,13 @@ class TenantUserPayload(BaseModel):
 
 def get_user(tenant_id: str, user_id: str | None) -> EndUser:
     """
-    Get current user
+    Get current user.
 
     NOTE: user_id is not trusted, it could be maliciously set to any value.
-    As a result, it could only be considered as an end user id.
+    As a result, it could only be considered as an end user id. Even when a
+    concrete end-user ID is supplied, lookups must stay tenant-scoped so one
+    tenant cannot bind another tenant's user record into the plugin request
+    context.
     """
     if not user_id:
         user_id = DefaultEndUserSessionID.DEFAULT_SESSION_ID
@@ -42,7 +45,14 @@ def get_user(tenant_id: str, user_id: str | None) -> EndUser:
                     .limit(1)
                 )
             else:
-                user_model = session.get(EndUser, user_id)
+                user_model = session.scalar(
+                    select(EndUser)
+                    .where(
+                        EndUser.id == user_id,
+                        EndUser.tenant_id == tenant_id,
+                    )
+                    .limit(1)
+                )
 
             if not user_model:
                 user_model = EndUser(

api/controllers/service_api/app/conversation.py

@@ -22,7 +22,7 @@ from fields.conversation_fields import (
     SimpleConversation,
 )
 from graphon.variables.types import SegmentType
-from libs.helper import UUIDStrOrEmpty
+from libs.helper import UUIDStrOrEmpty, to_timestamp
 from models.model import App, AppMode, EndUser
 from services.conversation_service import ConversationService
 
@@ -115,9 +115,7 @@ class ConversationVariableResponse(ResponseModel):
     @field_validator("created_at", "updated_at", mode="before")
     @classmethod
     def normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        if isinstance(value, datetime):
-            return int(value.timestamp())
-        return value
+        return to_timestamp(value)
 
 
 class ConversationVariableInfiniteScrollPaginationResponse(ResponseModel):

api/controllers/service_api/app/human_input_form.py

@@ -7,18 +7,18 @@ paused human input forms in workflow/chatflow runs.
 
 import json
 import logging
-from datetime import datetime
 
 from flask import Response
 from flask_restx import Resource
 from werkzeug.exceptions import BadRequest, NotFound
 
-from controllers.common.human_input import HumanInputFormSubmitPayload
+from controllers.common.human_input import HumanInputFormSubmitPayload, stringify_form_default_values
 from controllers.common.schema import register_schema_models
 from controllers.service_api import service_api_ns
 from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
 from core.workflow.human_input_policy import HumanInputSurface, is_recipient_type_allowed_for_surface
 from extensions.ext_database import db
+from libs.helper import to_timestamp
 from models.model import App, EndUser
 from services.human_input_service import Form, FormNotFoundError, HumanInputService
 
@@ -28,30 +28,14 @@ logger = logging.getLogger(__name__)
 register_schema_models(service_api_ns, HumanInputFormSubmitPayload)
 
 
-def _stringify_default_values(values: dict[str, object]) -> dict[str, str]:
-    result: dict[str, str] = {}
-    for key, value in values.items():
-        if value is None:
-            result[key] = ""
-        elif isinstance(value, (dict, list)):
-            result[key] = json.dumps(value, ensure_ascii=False)
-        else:
-            result[key] = str(value)
-    return result
-
-
-def _to_timestamp(value: datetime) -> int:
-    return int(value.timestamp())
-
-
 def _jsonify_form_definition(form: Form) -> Response:
     definition_payload = form.get_definition().model_dump()
     payload = {
         "form_content": definition_payload["rendered_content"],
         "inputs": definition_payload["inputs"],
-        "resolved_default_values": _stringify_default_values(definition_payload["default_values"]),
+        "resolved_default_values": stringify_form_default_values(definition_payload["default_values"]),
         "user_actions": definition_payload["user_actions"],
-        "expiration_time": _to_timestamp(form.expiration_time),
+        "expiration_time": to_timestamp(form.expiration_time),
     }
     return Response(json.dumps(payload, ensure_ascii=False), mimetype="application/json")
 

api/controllers/service_api/app/workflow.py

@@ -1,7 +1,7 @@
 import logging
 from collections.abc import Mapping
 from datetime import datetime
-from typing import Any, Literal
+from typing import Literal
 
 from dateutil.parser import isoparse
 from flask import request
@@ -39,6 +39,7 @@ from graphon.enums import WorkflowExecutionStatus
 from graphon.graph_engine.manager import GraphEngineManager
 from graphon.model_runtime.errors.invoke import InvokeError
 from libs import helper
+from libs.helper import to_timestamp
 from models.model import App, AppMode, EndUser
 from models.workflow import WorkflowRun
 from repositories.factory import DifyAPIRepositoryFactory
@@ -68,12 +69,6 @@ class WorkflowLogQuery(BaseModel):
 register_schema_models(service_api_ns, WorkflowRunPayload, WorkflowLogQuery)
 
 
-def _to_timestamp(value: datetime | int | None) -> int | None:
-    if isinstance(value, datetime):
-        return int(value.timestamp())
-    return value
-
-
 def _enum_value(value):
     return getattr(value, "value", value)
 
@@ -109,7 +104,7 @@ class WorkflowRunResponse(ResponseModel):
     @field_validator("created_at", "finished_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
+        return to_timestamp(value)
 
 
 class WorkflowRunForLogResponse(ResponseModel):
@@ -133,31 +128,13 @@ class WorkflowRunForLogResponse(ResponseModel):
     @field_validator("created_at", "finished_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
-
-
-class WorkflowAppLogEvaluationNodeInfoResponse(ResponseModel):
-    node_id: str
-    type: str
-    title: str
-
-
-class WorkflowAppLogEvaluationItemResponse(ResponseModel):
-    name: str
-    value: Any = None
-    details: dict[str, Any] | None = None
-    node_info: WorkflowAppLogEvaluationNodeInfoResponse | None = Field(
-        default=None,
-        validation_alias="node_info",
-        serialization_alias="nodeInfo",
-    )
+        return to_timestamp(value)
 
 
 class WorkflowAppLogPartialResponse(ResponseModel):
     id: str
     workflow_run: WorkflowRunForLogResponse | None = None
     details: dict | list | str | int | float | bool | None = None
-    evaluation: list[WorkflowAppLogEvaluationItemResponse] = Field(default_factory=list)
     created_from: str | None = None
     created_by_role: str | None = None
     created_by_account: SimpleAccount | None = None
@@ -172,12 +149,7 @@ class WorkflowAppLogPartialResponse(ResponseModel):
     @field_validator("created_at", mode="before")
     @classmethod
     def _normalize_timestamp(cls, value: datetime | int | None) -> int | None:
-        return _to_timestamp(value)
-
-    @field_validator("evaluation", mode="before")
-    @classmethod
-    def _normalize_evaluation(cls, value: Any) -> list[dict[str, Any]] | list[WorkflowAppLogEvaluationItemResponse]:
-        return value or []
+        return to_timestamp(value)
 
 
 class WorkflowAppLogPaginationResponse(ResponseModel):
@@ -192,8 +164,6 @@ register_schema_models(
     service_api_ns,
     WorkflowRunResponse,
     WorkflowRunForLogResponse,
-    WorkflowAppLogEvaluationNodeInfoResponse,
-    WorkflowAppLogEvaluationItemResponse,
     WorkflowAppLogPartialResponse,
     WorkflowAppLogPaginationResponse,
 )

api/controllers/service_api/dataset/dataset.py

@@ -31,7 +31,9 @@ from services.tag_service import (
     TagBindingCreatePayload,
     TagBindingDeletePayload,
     TagService,
-    UpdateTagPayload,
+)
+from services.tag_service import (
+    UpdateTagPayload as UpdateTagServicePayload,
 )
 
 register_enum_models(service_api_ns, DatasetPermissionEnum)
@@ -556,7 +558,7 @@ class DatasetTagsApi(DatasetApiResource):
 
         payload = TagUpdatePayload.model_validate(service_api_ns.payload or {})
         tag_id = payload.tag_id
-        tag = TagService.update_tags(UpdateTagPayload(name=payload.name, type=TagType.KNOWLEDGE), tag_id)
+        tag = TagService.update_tags(UpdateTagServicePayload(name=payload.name), tag_id)
 
         binding_count = TagService.get_tag_binding_count(tag_id)
 

api/controllers/web/__init__.py

@@ -23,7 +23,6 @@ from . import (
     feature,
     files,
     forgot_password,
-    human_input_file_upload,
     human_input_form,
     login,
     message,
@@ -47,7 +46,6 @@ __all__ = [
     "feature",
     "files",
     "forgot_password",
-    "human_input_file_upload",
     "human_input_form",
     "login",
     "message",

api/controllers/web/human_input_file_upload.py

@@ -1,181 +0,0 @@
-import httpx
-from flask import request
-from flask_restx import Resource
-from pydantic import BaseModel, Field, HttpUrl
-
-import services
-from controllers.common import helpers
-from controllers.common.errors import (
-    BlockedFileExtensionError,
-    FileTooLargeError,
-    NoFileUploadedError,
-    RemoteFileUploadError,
-    TooManyFilesError,
-    UnsupportedFileTypeError,
-)
-from controllers.common.schema import register_schema_models
-from controllers.web import web_ns
-from core.helper import ssrf_proxy
-from extensions.ext_database import db
-from fields.file_fields import FileResponse, FileWithSignedUrl
-from graphon.file import helpers as file_helpers
-from libs.exception import BaseHTTPException
-from services.file_service import FileService
-from services.human_input_file_upload_service import (
-    HITL_UPLOAD_TOKEN_PREFIX,
-    HumanInputFileUploadService,
-    InvalidUploadTokenError,
-)
-
-
-class InvalidUploadTokenBadRequestError(BaseHTTPException):
-    error_code = "invalid_upload_token"
-    description = "Invalid upload token."
-    code = 400
-
-
-class InvalidUploadTokenUnauthorizedError(BaseHTTPException):
-    error_code = "invalid_upload_token"
-    description = "Upload token is required."
-    code = 401
-
-
-class InvalidUploadTokenForbiddenError(BaseHTTPException):
-    error_code = "invalid_upload_token"
-    description = "Upload token is invalid or expired."
-    code = 403
-
-
-class HumanInputRemoteFileUploadPayload(BaseModel):
-    url: HttpUrl = Field(description="Remote file URL")
-
-
-register_schema_models(web_ns, HumanInputRemoteFileUploadPayload, FileResponse, FileWithSignedUrl)
-
-
-def _extract_hitl_upload_token() -> str:
-    """Read HITL upload token from Authorization without invoking other bearer auth chains."""
-
-    authorization = request.headers.get("Authorization")
-    if authorization is None:
-        raise InvalidUploadTokenUnauthorizedError()
-
-    parts = authorization.split()
-    if len(parts) != 2:
-        raise InvalidUploadTokenUnauthorizedError()
-
-    scheme, token = parts
-    if scheme.lower() != "bearer":
-        raise InvalidUploadTokenBadRequestError()
-    if not token:
-        raise InvalidUploadTokenUnauthorizedError()
-    if not token.startswith(HITL_UPLOAD_TOKEN_PREFIX):
-        raise InvalidUploadTokenBadRequestError()
-    return token
-
-
-def _validate_context(service: HumanInputFileUploadService, token: str):
-    try:
-        return service.validate_upload_token(token)
-    except InvalidUploadTokenError as exc:
-        raise InvalidUploadTokenForbiddenError() from exc
-
-
-def _parse_local_upload_file():
-    if "file" not in request.files:
-        raise NoFileUploadedError()
-    if len(request.files) > 1:
-        raise TooManyFilesError()
-
-    file = request.files["file"]
-    if not file.filename:
-        from controllers.common.errors import FilenameNotExistsError
-
-        raise FilenameNotExistsError()
-
-    return file
-
-
-@web_ns.route("/form/human_input/files/upload")
-class HumanInputFileUploadApi(Resource):
-    def post(self):
-        """Upload one local file for a HITL human input form."""
-
-        token = _extract_hitl_upload_token()
-        upload_service = HumanInputFileUploadService(db.engine)
-        context = _validate_context(upload_service, token)
-        file = _parse_local_upload_file()
-
-        try:
-            upload_file = FileService(db.engine).upload_file(
-                filename=file.filename or "",
-                content=file.read(),
-                mimetype=file.mimetype,
-                user=context.owner,
-                source=None,
-            )
-        except services.errors.file.FileTooLargeError as file_too_large_error:
-            raise FileTooLargeError(file_too_large_error.description)
-        except services.errors.file.UnsupportedFileTypeError:
-            raise UnsupportedFileTypeError()
-        except services.errors.file.BlockedFileExtensionError as exc:
-            raise BlockedFileExtensionError() from exc
-
-        upload_service.record_upload_file(context=context, file_id=upload_file.id)
-        response = FileResponse.model_validate(upload_file, from_attributes=True)
-        return response.model_dump(mode="json"), 201
-
-
-@web_ns.route("/form/human_input/files/remote-upload")
-class HumanInputRemoteFileUploadApi(Resource):
-    def post(self):
-        """Upload one remote URL file for a HITL human input form."""
-
-        token = _extract_hitl_upload_token()
-        upload_service = HumanInputFileUploadService(db.engine)
-        context = _validate_context(upload_service, token)
-        payload = HumanInputRemoteFileUploadPayload.model_validate(request.get_json(silent=True) or {})
-        url = str(payload.url)
-
-        try:
-            resp = ssrf_proxy.head(url=url)
-            if resp.status_code != httpx.codes.OK:
-                resp = ssrf_proxy.get(url=url, timeout=3, follow_redirects=True)
-            if resp.status_code != httpx.codes.OK:
-                raise RemoteFileUploadError(f"Failed to fetch file from {url}: {resp.text}")
-        except httpx.RequestError as exc:
-            raise RemoteFileUploadError(f"Failed to fetch file from {url}: {str(exc)}")
-
-        file_info = helpers.guess_file_info_from_response(resp)
-        if not FileService.is_file_size_within_limit(extension=file_info.extension, file_size=file_info.size):
-            raise FileTooLargeError()
-
-        content = resp.content if resp.request.method == "GET" else ssrf_proxy.get(url).content
-
-        try:
-            upload_file = FileService(db.engine).upload_file(
-                filename=file_info.filename,
-                content=content,
-                mimetype=file_info.mimetype,
-                user=context.owner,
-                source_url=url,
-            )
-        except services.errors.file.FileTooLargeError as file_too_large_error:
-            raise FileTooLargeError(file_too_large_error.description)
-        except services.errors.file.UnsupportedFileTypeError:
-            raise UnsupportedFileTypeError()
-        except services.errors.file.BlockedFileExtensionError as exc:
-            raise BlockedFileExtensionError() from exc
-
-        upload_service.record_upload_file(context=context, file_id=upload_file.id)
-        payload1 = FileWithSignedUrl(
-            id=upload_file.id,
-            name=upload_file.name,
-            size=upload_file.size,
-            extension=upload_file.extension,
-            url=file_helpers.get_signed_file_url(upload_file_id=upload_file.id),
-            mime_type=upload_file.mime_type,
-            created_by=upload_file.created_by,
-            created_at=int(upload_file.created_at.timestamp()),
-        )
-        return payload1.model_dump(mode="json"), 201

api/controllers/web/human_input_form.py

@@ -4,39 +4,27 @@ Web App Human Input Form APIs.
 
 import json
 import logging
-from datetime import datetime
 from typing import Any, NotRequired, TypedDict
 
 from flask import Response, request
 from flask_restx import Resource
-from pydantic import BaseModel
 from sqlalchemy import select
 from werkzeug.exceptions import Forbidden
 
 from configs import dify_config
-from controllers.common.human_input import HumanInputFormSubmitPayload
-from controllers.common.schema import register_schema_models
+from controllers.common.human_input import HumanInputFormSubmitPayload, stringify_form_default_values
 from controllers.web import web_ns
 from controllers.web.error import NotFoundError, WebFormRateLimitExceededError
 from controllers.web.site import serialize_app_site_payload
 from extensions.ext_database import db
-from libs.helper import RateLimiter, extract_remote_ip
+from libs.helper import RateLimiter, extract_remote_ip, to_timestamp
 from models.account import TenantStatus
 from models.model import App, Site
-from services.human_input_file_upload_service import HumanInputFileUploadService
 from services.human_input_service import Form, FormNotFoundError, HumanInputService
 
 logger = logging.getLogger(__name__)
 
 
-class HumanInputUploadTokenResponse(BaseModel):
-    upload_token: str
-    expires_at: int
-
-
-register_schema_models(web_ns, HumanInputUploadTokenResponse)
-
-
 _FORM_SUBMIT_RATE_LIMITER = RateLimiter(
     prefix="web_form_submit_rate_limit",
     max_attempts=dify_config.WEB_FORM_SUBMIT_RATE_LIMIT_MAX_ATTEMPTS,
@@ -47,27 +35,6 @@ _FORM_ACCESS_RATE_LIMITER = RateLimiter(
     max_attempts=dify_config.WEB_FORM_SUBMIT_RATE_LIMIT_MAX_ATTEMPTS,
     time_window=dify_config.WEB_FORM_SUBMIT_RATE_LIMIT_WINDOW_SECONDS,
 )
-_FORM_UPLOAD_TOKEN_RATE_LIMITER = RateLimiter(
-    prefix="web_form_upload_token_rate_limit",
-    max_attempts=dify_config.WEB_FORM_SUBMIT_RATE_LIMIT_MAX_ATTEMPTS,
-    time_window=dify_config.WEB_FORM_SUBMIT_RATE_LIMIT_WINDOW_SECONDS,
-)
-
-
-def _stringify_default_values(values: dict[str, object]) -> dict[str, str]:
-    result: dict[str, str] = {}
-    for key, value in values.items():
-        if value is None:
-            result[key] = ""
-        elif isinstance(value, (dict, list)):
-            result[key] = json.dumps(value, ensure_ascii=False)
-        else:
-            result[key] = str(value)
-    return result
-
-
-def _to_timestamp(value: datetime) -> int:
-    return int(value.timestamp())
 
 
 class FormDefinitionPayload(TypedDict):
@@ -85,42 +52,15 @@ def _jsonify_form_definition(form: Form, site_payload: dict | None = None) -> Re
     payload: FormDefinitionPayload = {
         "form_content": definition_payload["rendered_content"],
         "inputs": definition_payload["inputs"],
-        "resolved_default_values": _stringify_default_values(definition_payload["default_values"]),
+        "resolved_default_values": stringify_form_default_values(definition_payload["default_values"]),
         "user_actions": definition_payload["user_actions"],
-        "expiration_time": _to_timestamp(form.expiration_time),
+        "expiration_time": to_timestamp(form.expiration_time),
     }
     if site_payload is not None:
         payload["site"] = site_payload
     return Response(json.dumps(payload, ensure_ascii=False), mimetype="application/json")
 
 
-@web_ns.route("/form/human_input/<string:form_token>/upload-token")
-class HumanInputFormUploadTokenApi(Resource):
-    """API for issuing HITL upload tokens for active human input forms."""
-
-    def post(self, form_token: str):
-        """
-        Issue an upload token for a human input form.
-
-        POST /api/form/human_input/<form_token>/upload-token
-        """
-        ip_address = extract_remote_ip(request)
-        if _FORM_UPLOAD_TOKEN_RATE_LIMITER.is_rate_limited(ip_address):
-            raise WebFormRateLimitExceededError()
-        _FORM_UPLOAD_TOKEN_RATE_LIMITER.increment_rate_limit(ip_address)
-
-        try:
-            token = HumanInputFileUploadService(db.engine).issue_upload_token(form_token)
-        except FormNotFoundError:
-            raise NotFoundError("Form not found")
-
-        response = HumanInputUploadTokenResponse(
-            upload_token=token.upload_token,
-            expires_at=_to_timestamp(token.expires_at),
-        )
-        return response.model_dump(mode="json"), 200
-
-
 @web_ns.route("/form/human_input/<string:form_token>")
 class HumanInputFormApi(Resource):
     """API for getting and submitting human input forms via the web app."""

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -9,7 +9,7 @@ from datetime import datetime
 from threading import Thread
 from typing import Any, Union
 
-from sqlalchemy import select
+from sqlalchemy import select, update
 from sqlalchemy.orm import Session, sessionmaker
 
 from constants.tts_auto_play_timeout import TTS_AUTO_PLAY_TIMEOUT, TTS_AUTO_PLAY_YIELD_CPU_TIME
@@ -245,49 +245,50 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
         """
         human_input_responses: list[HumanInputRequiredResponse] = []
         for stream_response in generator:
-            if isinstance(stream_response, ErrorStreamResponse):
-                raise stream_response.err
-            elif isinstance(stream_response, HumanInputRequiredResponse):
-                human_input_responses.append(stream_response)
-            elif isinstance(stream_response, WorkflowPauseStreamResponse):
-                return AdvancedChatPausedBlockingResponse(
-                    task_id=stream_response.task_id,
-                    data=AdvancedChatPausedBlockingResponse.Data(
-                        id=self._message_id,
-                        mode=self._conversation_mode,
-                        conversation_id=self._conversation_id,
-                        message_id=self._message_id,
-                        workflow_run_id=stream_response.data.workflow_run_id,
-                        answer=self._task_state.answer,
-                        metadata=self._message_end_to_stream_response().metadata,
-                        created_at=self._message_created_at,
-                        paused_nodes=stream_response.data.paused_nodes,
-                        reasons=stream_response.data.reasons,
-                        status=stream_response.data.status,
-                        elapsed_time=stream_response.data.elapsed_time,
-                        total_tokens=stream_response.data.total_tokens,
-                        total_steps=stream_response.data.total_steps,
-                    ),
-                )
-            elif isinstance(stream_response, MessageEndStreamResponse):
-                extras = {}
-                if stream_response.metadata:
-                    extras["metadata"] = stream_response.metadata
+            match stream_response:
+                case ErrorStreamResponse():
+                    raise stream_response.err
+                case HumanInputRequiredResponse():
+                    human_input_responses.append(stream_response)
+                case WorkflowPauseStreamResponse():
+                    return AdvancedChatPausedBlockingResponse(
+                        task_id=stream_response.task_id,
+                        data=AdvancedChatPausedBlockingResponse.Data(
+                            id=self._message_id,
+                            mode=self._conversation_mode,
+                            conversation_id=self._conversation_id,
+                            message_id=self._message_id,
+                            workflow_run_id=stream_response.data.workflow_run_id,
+                            answer=self._task_state.answer,
+                            metadata=self._message_end_to_stream_response().metadata,
+                            created_at=self._message_created_at,
+                            paused_nodes=stream_response.data.paused_nodes,
+                            reasons=stream_response.data.reasons,
+                            status=stream_response.data.status,
+                            elapsed_time=stream_response.data.elapsed_time,
+                            total_tokens=stream_response.data.total_tokens,
+                            total_steps=stream_response.data.total_steps,
+                        ),
+                    )
+                case MessageEndStreamResponse():
+                    extras = {}
+                    if stream_response.metadata:
+                        extras["metadata"] = stream_response.metadata
 
-                return ChatbotAppBlockingResponse(
-                    task_id=stream_response.task_id,
-                    data=ChatbotAppBlockingResponse.Data(
-                        id=self._message_id,
-                        mode=self._conversation_mode,
-                        conversation_id=self._conversation_id,
-                        message_id=self._message_id,
-                        answer=self._task_state.answer,
-                        created_at=self._message_created_at,
-                        **extras,
-                    ),
-                )
-            else:
-                continue
+                    return ChatbotAppBlockingResponse(
+                        task_id=stream_response.task_id,
+                        data=ChatbotAppBlockingResponse.Data(
+                            id=self._message_id,
+                            mode=self._conversation_mode,
+                            conversation_id=self._conversation_id,
+                            message_id=self._message_id,
+                            answer=self._task_state.answer,
+                            created_at=self._message_created_at,
+                            **extras,
+                        ),
+                    )
+                case _:
+                    continue
 
         if human_input_responses:
             return self._build_paused_blocking_response_from_human_input(human_input_responses)
@@ -425,11 +426,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
         self._workflow_run_id = run_id
 
         with self._database_session() as session:
-            message = self._get_message(session=session)
-            if not message:
-                raise ValueError(f"Message not found: {self._message_id}")
-
-            message.workflow_run_id = run_id
+            session.execute(update(Message).where(Message.id == self._message_id).values(workflow_run_id=run_id))
 
         workflow_start_resp = self._workflow_response_converter.workflow_start_to_stream_response(
             task_id=self._application_generate_entity.task_id,

api/core/app/apps/agent_chat/app_config_manager.py

@@ -178,7 +178,7 @@ class AgentChatAppConfigManager(BaseAppConfigManager):
         if not isinstance(agent_mode, dict):
             raise ValueError("agent_mode must be of object type")
 
-        # FIXME(-LAN-): Cast needed due to basedpyright limitation with dict type narrowing
+        # FIXME(-LAN-): Cast needed because static checkers do not narrow this dict value.
         agent_mode = cast(dict[str, Any], agent_mode)
 
         if "enabled" not in agent_mode or not agent_mode["enabled"]:

api/core/app/apps/common/workflow_response_converter.py

@@ -408,19 +408,17 @@ class WorkflowResponseConverter:
         self, *, event: QueueHumanInputFormFilledEvent, task_id: str
     ) -> HumanInputFormFilledResponse:
         run_id = self._ensure_workflow_run_id()
-        data = HumanInputFormFilledResponse.Data(
-            node_id=event.node_id,
-            node_title=event.node_title,
-            rendered_content=event.rendered_content,
-            action_id=event.action_id,
-            action_text=event.action_text,
+        return HumanInputFormFilledResponse(
+            task_id=task_id,
+            workflow_run_id=run_id,
+            data=HumanInputFormFilledResponse.Data(
+                node_id=event.node_id,
+                node_title=event.node_title,
+                rendered_content=event.rendered_content,
+                action_id=event.action_id,
+                action_text=event.action_text,
+            ),
         )
-        if event.submitted_data is not None:
-            runtime_type_converter = WorkflowRuntimeTypeConverter()
-
-            data.submitted_data = runtime_type_converter.value_to_json_encodable_recursive(event.submitted_data)
-
-        return HumanInputFormFilledResponse(task_id=task_id, workflow_run_id=run_id, data=data)
 
     def human_input_form_timeout_to_stream_response(
         self, *, event: QueueHumanInputFormTimeoutEvent, task_id: str

api/core/app/apps/pipeline/generate_response_converter.py

@@ -45,20 +45,24 @@ class WorkflowAppGenerateResponseConverter(AppGenerateResponseConverter[Workflow
             chunk = cast(WorkflowAppStreamResponse, chunk)
             sub_stream_response = chunk.stream_response
 
-            if isinstance(sub_stream_response, PingStreamResponse):
-                yield "ping"
-                continue
+            match sub_stream_response:
+                case PingStreamResponse():
+                    yield "ping"
+                    continue
+                case ErrorStreamResponse():
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    data = cls._error_to_stream_response(sub_stream_response.err)
+                    response_chunk.update(cast(dict, data))
+                case _:
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    response_chunk.update(sub_stream_response.model_dump())
 
-            response_chunk = {
-                "event": sub_stream_response.event.value,
-                "workflow_run_id": chunk.workflow_run_id,
-            }
-
-            if isinstance(sub_stream_response, ErrorStreamResponse):
-                data = cls._error_to_stream_response(sub_stream_response.err)
-                response_chunk.update(cast(dict, data))
-            else:
-                response_chunk.update(sub_stream_response.model_dump())
             yield response_chunk
 
     @classmethod
@@ -74,20 +78,28 @@ class WorkflowAppGenerateResponseConverter(AppGenerateResponseConverter[Workflow
             chunk = cast(WorkflowAppStreamResponse, chunk)
             sub_stream_response = chunk.stream_response
 
-            if isinstance(sub_stream_response, PingStreamResponse):
-                yield "ping"
-                continue
+            match sub_stream_response:
+                case PingStreamResponse():
+                    yield "ping"
+                    continue
+                case ErrorStreamResponse():
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    data = cls._error_to_stream_response(sub_stream_response.err)
+                    response_chunk.update(cast(dict, data))
+                case NodeStartStreamResponse() | NodeFinishStreamResponse():
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    response_chunk.update(cast(dict, sub_stream_response.to_ignore_detail_dict()))
+                case _:
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    response_chunk.update(sub_stream_response.model_dump())
 
-            response_chunk = {
-                "event": sub_stream_response.event.value,
-                "workflow_run_id": chunk.workflow_run_id,
-            }
-
-            if isinstance(sub_stream_response, ErrorStreamResponse):
-                data = cls._error_to_stream_response(sub_stream_response.err)
-                response_chunk.update(cast(dict, data))
-            elif isinstance(sub_stream_response, NodeStartStreamResponse | NodeFinishStreamResponse):
-                response_chunk.update(cast(dict, sub_stream_response.to_ignore_detail_dict()))
-            else:
-                response_chunk.update(sub_stream_response.model_dump())
             yield response_chunk

api/core/app/apps/workflow/app_generator.py

@@ -10,7 +10,7 @@ from typing import TYPE_CHECKING, Any, Literal, overload
 from flask import Flask, current_app
 from pydantic import ValidationError
 from sqlalchemy import select
-from sqlalchemy.orm import Session, sessionmaker
+from sqlalchemy.orm import sessionmaker
 
 import contexts
 from configs import dify_config
@@ -58,25 +58,6 @@ logger = logging.getLogger(__name__)
 
 
 class WorkflowAppGenerator(BaseAppGenerator):
-    @staticmethod
-    def _ensure_snippet_start_node_in_worker(*, session: Session, workflow: Workflow) -> Workflow:
-        """Re-apply snippet virtual Start injection after worker reloads workflow from DB."""
-        if workflow.kind_or_standard != "snippet":
-            return workflow
-
-        from models.snippet import CustomizedSnippet
-        from services.snippet_generate_service import SnippetGenerateService
-
-        snippet = session.scalar(
-            select(CustomizedSnippet).where(
-                CustomizedSnippet.id == workflow.app_id,
-                CustomizedSnippet.tenant_id == workflow.tenant_id,
-            )
-        )
-        if snippet is None:
-            return workflow
-        return SnippetGenerateService.ensure_start_node_for_worker(workflow, snippet)
-
     @staticmethod
     def _should_prepare_user_inputs(args: Mapping[str, Any]) -> bool:
         return not bool(args.get(SKIP_PREPARE_USER_INPUTS_KEY))
@@ -594,8 +575,6 @@ class WorkflowAppGenerator(BaseAppGenerator):
                 if workflow is None:
                     raise ValueError("Workflow not found")
 
-                workflow = self._ensure_snippet_start_node_in_worker(session=session, workflow=workflow)
-
                 # Determine system_user_id based on invocation source
                 is_external_api_call = application_generate_entity.invoke_from in {
                     InvokeFrom.WEB_APP,

api/core/app/apps/workflow/app_runner.py

@@ -10,7 +10,6 @@ from core.app.entities.app_invoke_entities import InvokeFrom, WorkflowAppGenerat
 from core.app.workflow.layers.persistence import PersistenceWorkflowInfo, WorkflowPersistenceLayer
 from core.repositories.factory import WorkflowExecutionRepository, WorkflowNodeExecutionRepository
 from core.workflow.node_factory import get_default_root_node_id
-from core.workflow.snippet_start import get_compatible_start_aliases
 from core.workflow.system_variables import build_bootstrap_variables, build_system_variables
 from core.workflow.variable_pool_initializer import add_node_inputs_to_pool, add_variables_to_pool
 from core.workflow.workflow_entry import WorkflowEntry
@@ -116,15 +115,7 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
                 ),
             )
             root_node_id = self._root_node_id or get_default_root_node_id(self._workflow.graph_dict)
-            add_node_inputs_to_pool(
-                variable_pool,
-                node_id=root_node_id,
-                inputs=inputs,
-                aliases=get_compatible_start_aliases(
-                    workflow_kind=getattr(self._workflow, "kind_or_standard", None),
-                    root_node_id=root_node_id,
-                ),
-            )
+            add_node_inputs_to_pool(variable_pool, node_id=root_node_id, inputs=inputs)
 
             graph_runtime_state = GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter())
             graph = self._init_graph(

api/core/app/apps/workflow/generate_response_converter.py

@@ -52,20 +52,24 @@ class WorkflowAppGenerateResponseConverter(
             chunk = cast(WorkflowAppStreamResponse, chunk)
             sub_stream_response = chunk.stream_response
 
-            if isinstance(sub_stream_response, PingStreamResponse):
-                yield "ping"
-                continue
+            match sub_stream_response:
+                case PingStreamResponse():
+                    yield "ping"
+                    continue
+                case ErrorStreamResponse():
+                    response_chunk: dict[str, object] = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    data = cls._error_to_stream_response(sub_stream_response.err)
+                    response_chunk.update(data)
+                case _:
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    response_chunk.update(sub_stream_response.model_dump(mode="json"))
 
-            response_chunk: dict[str, object] = {
-                "event": sub_stream_response.event.value,
-                "workflow_run_id": chunk.workflow_run_id,
-            }
-
-            if isinstance(sub_stream_response, ErrorStreamResponse):
-                data = cls._error_to_stream_response(sub_stream_response.err)
-                response_chunk.update(data)
-            else:
-                response_chunk.update(sub_stream_response.model_dump(mode="json"))
             yield response_chunk
 
     @classmethod
@@ -81,20 +85,28 @@ class WorkflowAppGenerateResponseConverter(
             chunk = cast(WorkflowAppStreamResponse, chunk)
             sub_stream_response = chunk.stream_response
 
-            if isinstance(sub_stream_response, PingStreamResponse):
-                yield "ping"
-                continue
+            match sub_stream_response:
+                case PingStreamResponse():
+                    yield "ping"
+                    continue
+                case ErrorStreamResponse():
+                    response_chunk: dict[str, object] = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    data = cls._error_to_stream_response(sub_stream_response.err)
+                    response_chunk.update(data)
+                case NodeStartStreamResponse() | NodeFinishStreamResponse():
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    response_chunk.update(sub_stream_response.to_ignore_detail_dict())
+                case _:
+                    response_chunk = {
+                        "event": sub_stream_response.event.value,
+                        "workflow_run_id": chunk.workflow_run_id,
+                    }
+                    response_chunk.update(sub_stream_response.model_dump(mode="json"))
 
-            response_chunk: dict[str, object] = {
-                "event": sub_stream_response.event.value,
-                "workflow_run_id": chunk.workflow_run_id,
-            }
-
-            if isinstance(sub_stream_response, ErrorStreamResponse):
-                data = cls._error_to_stream_response(sub_stream_response.err)
-                response_chunk.update(data)
-            elif isinstance(sub_stream_response, NodeStartStreamResponse | NodeFinishStreamResponse):
-                response_chunk.update(sub_stream_response.to_ignore_detail_dict())
-            else:
-                response_chunk.update(sub_stream_response.model_dump(mode="json"))
             yield response_chunk

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -145,50 +145,51 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
         """
         human_input_responses: list[HumanInputRequiredResponse] = []
         for stream_response in generator:
-            if isinstance(stream_response, ErrorStreamResponse):
-                raise stream_response.err
-            elif isinstance(stream_response, HumanInputRequiredResponse):
-                human_input_responses.append(stream_response)
-            elif isinstance(stream_response, WorkflowPauseStreamResponse):
-                return WorkflowAppPausedBlockingResponse(
-                    task_id=self._application_generate_entity.task_id,
-                    workflow_run_id=stream_response.data.workflow_run_id,
-                    data=WorkflowAppPausedBlockingResponse.Data(
-                        id=stream_response.data.workflow_run_id,
-                        workflow_id=self._workflow.id,
-                        status=stream_response.data.status,
-                        outputs=stream_response.data.outputs or {},
-                        error=None,
-                        elapsed_time=stream_response.data.elapsed_time,
-                        total_tokens=stream_response.data.total_tokens,
-                        total_steps=stream_response.data.total_steps,
-                        created_at=stream_response.data.created_at,
-                        finished_at=None,
-                        paused_nodes=stream_response.data.paused_nodes,
-                        reasons=stream_response.data.reasons,
-                    ),
-                )
-
-            elif isinstance(stream_response, WorkflowFinishStreamResponse):
-                return WorkflowAppBlockingResponse(
-                    task_id=self._application_generate_entity.task_id,
-                    workflow_run_id=stream_response.data.id,
-                    data=WorkflowAppBlockingResponse.Data(
-                        id=stream_response.data.id,
-                        workflow_id=stream_response.data.workflow_id,
-                        status=stream_response.data.status,
-                        outputs=stream_response.data.outputs,
-                        error=stream_response.data.error,
-                        elapsed_time=stream_response.data.elapsed_time,
-                        total_tokens=stream_response.data.total_tokens,
-                        total_steps=stream_response.data.total_steps,
-                        created_at=int(stream_response.data.created_at),
-                        finished_at=int(stream_response.data.finished_at) if stream_response.data.finished_at else None,
-                    ),
-                )
-
-            else:
-                continue
+            match stream_response:
+                case ErrorStreamResponse():
+                    raise stream_response.err
+                case HumanInputRequiredResponse():
+                    human_input_responses.append(stream_response)
+                case WorkflowPauseStreamResponse():
+                    return WorkflowAppPausedBlockingResponse(
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_run_id=stream_response.data.workflow_run_id,
+                        data=WorkflowAppPausedBlockingResponse.Data(
+                            id=stream_response.data.workflow_run_id,
+                            workflow_id=self._workflow.id,
+                            status=stream_response.data.status,
+                            outputs=stream_response.data.outputs or {},
+                            error=None,
+                            elapsed_time=stream_response.data.elapsed_time,
+                            total_tokens=stream_response.data.total_tokens,
+                            total_steps=stream_response.data.total_steps,
+                            created_at=stream_response.data.created_at,
+                            finished_at=None,
+                            paused_nodes=stream_response.data.paused_nodes,
+                            reasons=stream_response.data.reasons,
+                        ),
+                    )
+                case WorkflowFinishStreamResponse():
+                    return WorkflowAppBlockingResponse(
+                        task_id=self._application_generate_entity.task_id,
+                        workflow_run_id=stream_response.data.id,
+                        data=WorkflowAppBlockingResponse.Data(
+                            id=stream_response.data.id,
+                            workflow_id=stream_response.data.workflow_id,
+                            status=stream_response.data.status,
+                            outputs=stream_response.data.outputs,
+                            error=stream_response.data.error,
+                            elapsed_time=stream_response.data.elapsed_time,
+                            total_tokens=stream_response.data.total_tokens,
+                            total_steps=stream_response.data.total_steps,
+                            created_at=int(stream_response.data.created_at),
+                            finished_at=int(stream_response.data.finished_at)
+                            if stream_response.data.finished_at
+                            else None,
+                        ),
+                    )
+                case _:
+                    continue
 
         if human_input_responses:
             return self._build_paused_blocking_response_from_human_input(human_input_responses)

api/core/app/apps/workflow_app_runner.py

@@ -399,279 +399,281 @@ class WorkflowBasedAppRunner:
         :param workflow_entry: workflow entry
         :param event: event
         """
-        if isinstance(event, GraphRunStartedEvent):
-            self._publish_event(QueueWorkflowStartedEvent(reason=event.reason))
-        elif isinstance(event, GraphRunSucceededEvent):
-            self._publish_event(QueueWorkflowSucceededEvent(outputs=event.outputs))
-        elif isinstance(event, GraphRunPartialSucceededEvent):
-            self._publish_event(
-                QueueWorkflowPartialSuccessEvent(outputs=event.outputs, exceptions_count=event.exceptions_count)
-            )
-        elif isinstance(event, GraphRunFailedEvent):
-            self._publish_event(QueueWorkflowFailedEvent(error=event.error, exceptions_count=event.exceptions_count))
-        elif isinstance(event, GraphRunAbortedEvent):
-            self._publish_event(QueueWorkflowFailedEvent(error=event.reason or "Unknown error", exceptions_count=0))
-        elif isinstance(event, GraphRunPausedEvent):
-            runtime_state = workflow_entry.graph_engine.graph_runtime_state
-            paused_nodes = runtime_state.get_paused_nodes()
-            self._enqueue_human_input_notifications(event.reasons)
-            self._publish_event(
-                QueueWorkflowPausedEvent(
-                    reasons=event.reasons,
-                    outputs=event.outputs,
-                    paused_nodes=paused_nodes,
+        match event:
+            case GraphRunStartedEvent():
+                self._publish_event(QueueWorkflowStartedEvent(reason=event.reason))
+            case GraphRunSucceededEvent():
+                self._publish_event(QueueWorkflowSucceededEvent(outputs=event.outputs))
+            case GraphRunPartialSucceededEvent():
+                self._publish_event(
+                    QueueWorkflowPartialSuccessEvent(outputs=event.outputs, exceptions_count=event.exceptions_count)
                 )
-            )
-        elif isinstance(event, NodeRunHumanInputFormFilledEvent):
-            self._publish_event(
-                QueueHumanInputFormFilledEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    rendered_content=event.rendered_content,
-                    action_id=event.action_id,
-                    action_text=event.action_text,
-                    submitted_data=event.submitted_data,
+            case GraphRunFailedEvent():
+                self._publish_event(
+                    QueueWorkflowFailedEvent(error=event.error, exceptions_count=event.exceptions_count)
                 )
-            )
-        elif isinstance(event, NodeRunHumanInputFormTimeoutEvent):
-            self._publish_event(
-                QueueHumanInputFormTimeoutEvent(
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    expiration_time=event.expiration_time,
+            case GraphRunAbortedEvent():
+                self._publish_event(QueueWorkflowFailedEvent(error=event.reason or "Unknown error", exceptions_count=0))
+            case GraphRunPausedEvent():
+                runtime_state = workflow_entry.graph_engine.graph_runtime_state
+                paused_nodes = runtime_state.get_paused_nodes()
+                self._enqueue_human_input_notifications(event.reasons)
+                self._publish_event(
+                    QueueWorkflowPausedEvent(
+                        reasons=event.reasons,
+                        outputs=event.outputs,
+                        paused_nodes=paused_nodes,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunRetryEvent):
-            node_run_result = event.node_run_result
-            inputs = node_run_result.inputs
-            process_data = node_run_result.process_data
-            outputs = project_node_outputs_for_workflow_run(
-                node_type=event.node_type,
-                inputs=inputs,
-                outputs=node_run_result.outputs,
-            )
-            execution_metadata = node_run_result.metadata
-            self._publish_event(
-                QueueNodeRetryEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_title=event.node_title,
+            case NodeRunHumanInputFormFilledEvent():
+                self._publish_event(
+                    QueueHumanInputFormFilledEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        rendered_content=event.rendered_content,
+                        action_id=event.action_id,
+                        action_text=event.action_text,
+                    )
+                )
+            case NodeRunHumanInputFormTimeoutEvent():
+                self._publish_event(
+                    QueueHumanInputFormTimeoutEvent(
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        expiration_time=event.expiration_time,
+                    )
+                )
+            case NodeRunRetryEvent():
+                node_run_result = event.node_run_result
+                inputs = node_run_result.inputs
+                process_data = node_run_result.process_data
+                outputs = project_node_outputs_for_workflow_run(
                     node_type=event.node_type,
-                    start_at=event.start_at,
-                    in_iteration_id=event.in_iteration_id,
-                    in_loop_id=event.in_loop_id,
                     inputs=inputs,
-                    process_data=process_data,
-                    outputs=outputs,
-                    error=event.error,
-                    execution_metadata=execution_metadata,
-                    retry_index=event.retry_index,
-                    provider_type=event.provider_type,
-                    provider_id=event.provider_id,
+                    outputs=node_run_result.outputs,
                 )
-            )
-        elif isinstance(event, NodeRunStartedEvent):
-            self._publish_event(
-                QueueNodeStartedEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_title=event.node_title,
-                    node_type=event.node_type,
-                    start_at=event.start_at,
-                    in_iteration_id=event.in_iteration_id,
-                    in_loop_id=event.in_loop_id,
-                    agent_strategy=self._build_agent_strategy_info(event),
-                    provider_type=event.provider_type,
-                    provider_id=event.provider_id,
+                execution_metadata = node_run_result.metadata
+                self._publish_event(
+                    QueueNodeRetryEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_title=event.node_title,
+                        node_type=event.node_type,
+                        start_at=event.start_at,
+                        in_iteration_id=event.in_iteration_id,
+                        in_loop_id=event.in_loop_id,
+                        inputs=inputs,
+                        process_data=process_data,
+                        outputs=outputs,
+                        error=event.error,
+                        execution_metadata=execution_metadata,
+                        retry_index=event.retry_index,
+                        provider_type=event.provider_type,
+                        provider_id=event.provider_id,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunSucceededEvent):
-            node_run_result = event.node_run_result
-            inputs = node_run_result.inputs
-            process_data = node_run_result.process_data
-            outputs = project_node_outputs_for_workflow_run(
-                node_type=event.node_type,
-                inputs=inputs,
-                outputs=node_run_result.outputs,
-            )
-            execution_metadata = node_run_result.metadata
-            self._publish_event(
-                QueueNodeSucceededEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
+            case NodeRunStartedEvent():
+                self._publish_event(
+                    QueueNodeStartedEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_title=event.node_title,
+                        node_type=event.node_type,
+                        start_at=event.start_at,
+                        in_iteration_id=event.in_iteration_id,
+                        in_loop_id=event.in_loop_id,
+                        agent_strategy=self._build_agent_strategy_info(event),
+                        provider_type=event.provider_type,
+                        provider_id=event.provider_id,
+                    )
+                )
+            case NodeRunSucceededEvent():
+                node_run_result = event.node_run_result
+                inputs = node_run_result.inputs
+                process_data = node_run_result.process_data
+                outputs = project_node_outputs_for_workflow_run(
                     node_type=event.node_type,
-                    start_at=event.start_at,
-                    finished_at=event.finished_at,
                     inputs=inputs,
-                    process_data=process_data,
-                    outputs=outputs,
-                    execution_metadata=execution_metadata,
-                    in_iteration_id=event.in_iteration_id,
-                    in_loop_id=event.in_loop_id,
+                    outputs=node_run_result.outputs,
                 )
-            )
-        elif isinstance(event, NodeRunFailedEvent):
-            outputs = project_node_outputs_for_workflow_run(
-                node_type=event.node_type,
-                inputs=event.node_run_result.inputs,
-                outputs=event.node_run_result.outputs,
-            )
-            self._publish_event(
-                QueueNodeFailedEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
+                execution_metadata = node_run_result.metadata
+                self._publish_event(
+                    QueueNodeSucceededEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        start_at=event.start_at,
+                        finished_at=event.finished_at,
+                        inputs=inputs,
+                        process_data=process_data,
+                        outputs=outputs,
+                        execution_metadata=execution_metadata,
+                        in_iteration_id=event.in_iteration_id,
+                        in_loop_id=event.in_loop_id,
+                    )
+                )
+            case NodeRunFailedEvent():
+                outputs = project_node_outputs_for_workflow_run(
                     node_type=event.node_type,
-                    start_at=event.start_at,
-                    finished_at=event.finished_at,
                     inputs=event.node_run_result.inputs,
-                    process_data=event.node_run_result.process_data,
-                    outputs=outputs,
-                    error=event.node_run_result.error or "Unknown error",
-                    execution_metadata=event.node_run_result.metadata,
-                    in_iteration_id=event.in_iteration_id,
-                    in_loop_id=event.in_loop_id,
+                    outputs=event.node_run_result.outputs,
                 )
-            )
-        elif isinstance(event, NodeRunExceptionEvent):
-            outputs = project_node_outputs_for_workflow_run(
-                node_type=event.node_type,
-                inputs=event.node_run_result.inputs,
-                outputs=event.node_run_result.outputs,
-            )
-            self._publish_event(
-                QueueNodeExceptionEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
+                self._publish_event(
+                    QueueNodeFailedEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        start_at=event.start_at,
+                        finished_at=event.finished_at,
+                        inputs=event.node_run_result.inputs,
+                        process_data=event.node_run_result.process_data,
+                        outputs=outputs,
+                        error=event.node_run_result.error or "Unknown error",
+                        execution_metadata=event.node_run_result.metadata,
+                        in_iteration_id=event.in_iteration_id,
+                        in_loop_id=event.in_loop_id,
+                    )
+                )
+            case NodeRunExceptionEvent():
+                outputs = project_node_outputs_for_workflow_run(
                     node_type=event.node_type,
-                    start_at=event.start_at,
-                    finished_at=event.finished_at,
                     inputs=event.node_run_result.inputs,
-                    process_data=event.node_run_result.process_data,
-                    outputs=outputs,
-                    error=event.node_run_result.error or "Unknown error",
-                    execution_metadata=event.node_run_result.metadata,
-                    in_iteration_id=event.in_iteration_id,
-                    in_loop_id=event.in_loop_id,
+                    outputs=event.node_run_result.outputs,
                 )
-            )
-        elif isinstance(event, NodeRunStreamChunkEvent):
-            self._publish_event(
-                QueueTextChunkEvent(
-                    text=event.chunk,
-                    from_variable_selector=list(event.selector),
-                    in_iteration_id=event.in_iteration_id,
-                    in_loop_id=event.in_loop_id,
+                self._publish_event(
+                    QueueNodeExceptionEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        start_at=event.start_at,
+                        finished_at=event.finished_at,
+                        inputs=event.node_run_result.inputs,
+                        process_data=event.node_run_result.process_data,
+                        outputs=outputs,
+                        error=event.node_run_result.error or "Unknown error",
+                        execution_metadata=event.node_run_result.metadata,
+                        in_iteration_id=event.in_iteration_id,
+                        in_loop_id=event.in_loop_id,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunRetrieverResourceEvent):
-            self._publish_event(
-                QueueRetrieverResourcesEvent(
-                    retriever_resources=[
-                        RetrievalSourceMetadata.model_validate(resource) for resource in event.retriever_resources
-                    ],
-                    in_iteration_id=event.in_iteration_id,
-                    in_loop_id=event.in_loop_id,
+            case NodeRunStreamChunkEvent():
+                self._publish_event(
+                    QueueTextChunkEvent(
+                        text=event.chunk,
+                        from_variable_selector=list(event.selector),
+                        in_iteration_id=event.in_iteration_id,
+                        in_loop_id=event.in_loop_id,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunAgentLogEvent):
-            self._publish_event(
-                QueueAgentLogEvent(
-                    id=event.message_id,
-                    label=event.label,
-                    node_execution_id=event.node_execution_id,
-                    parent_id=event.parent_id,
-                    error=event.error,
-                    status=event.status,
-                    data=event.data,
-                    metadata=event.metadata,
-                    node_id=event.node_id,
+            case NodeRunRetrieverResourceEvent():
+                self._publish_event(
+                    QueueRetrieverResourcesEvent(
+                        retriever_resources=[
+                            RetrievalSourceMetadata.model_validate(resource) for resource in event.retriever_resources
+                        ],
+                        in_iteration_id=event.in_iteration_id,
+                        in_loop_id=event.in_loop_id,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunIterationStartedEvent):
-            self._publish_event(
-                QueueIterationStartEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    start_at=event.start_at,
-                    node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
-                    inputs=event.inputs,
-                    metadata=event.metadata,
+            case NodeRunAgentLogEvent():
+                self._publish_event(
+                    QueueAgentLogEvent(
+                        id=event.message_id,
+                        label=event.label,
+                        node_execution_id=event.node_execution_id,
+                        parent_id=event.parent_id,
+                        error=event.error,
+                        status=event.status,
+                        data=event.data,
+                        metadata=event.metadata,
+                        node_id=event.node_id,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunIterationNextEvent):
-            self._publish_event(
-                QueueIterationNextEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    index=event.index,
-                    node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
-                    output=event.pre_iteration_output,
+            case NodeRunIterationStartedEvent():
+                self._publish_event(
+                    QueueIterationStartEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        start_at=event.start_at,
+                        node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
+                        inputs=event.inputs,
+                        metadata=event.metadata,
+                    )
                 )
-            )
-        elif isinstance(event, (NodeRunIterationSucceededEvent | NodeRunIterationFailedEvent)):
-            self._publish_event(
-                QueueIterationCompletedEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    start_at=event.start_at,
-                    node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
-                    inputs=event.inputs,
-                    outputs=event.outputs,
-                    metadata=event.metadata,
-                    steps=event.steps,
-                    error=event.error if isinstance(event, NodeRunIterationFailedEvent) else None,
+            case NodeRunIterationNextEvent():
+                self._publish_event(
+                    QueueIterationNextEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        index=event.index,
+                        node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
+                        output=event.pre_iteration_output,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunLoopStartedEvent):
-            self._publish_event(
-                QueueLoopStartEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    start_at=event.start_at,
-                    node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
-                    inputs=event.inputs,
-                    metadata=event.metadata,
+            case NodeRunIterationSucceededEvent() | NodeRunIterationFailedEvent():
+                self._publish_event(
+                    QueueIterationCompletedEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        start_at=event.start_at,
+                        node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
+                        inputs=event.inputs,
+                        outputs=event.outputs,
+                        metadata=event.metadata,
+                        steps=event.steps,
+                        error=event.error if isinstance(event, NodeRunIterationFailedEvent) else None,
+                    )
                 )
-            )
-        elif isinstance(event, NodeRunLoopNextEvent):
-            self._publish_event(
-                QueueLoopNextEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    index=event.index,
-                    node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
-                    output=event.pre_loop_output,
+            case NodeRunLoopStartedEvent():
+                self._publish_event(
+                    QueueLoopStartEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        start_at=event.start_at,
+                        node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
+                        inputs=event.inputs,
+                        metadata=event.metadata,
+                    )
                 )
-            )
-        elif isinstance(event, (NodeRunLoopSucceededEvent | NodeRunLoopFailedEvent)):
-            self._publish_event(
-                QueueLoopCompletedEvent(
-                    node_execution_id=event.id,
-                    node_id=event.node_id,
-                    node_type=event.node_type,
-                    node_title=event.node_title,
-                    start_at=event.start_at,
-                    node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
-                    inputs=event.inputs,
-                    outputs=event.outputs,
-                    metadata=event.metadata,
-                    steps=event.steps,
-                    error=event.error if isinstance(event, NodeRunLoopFailedEvent) else None,
+            case NodeRunLoopNextEvent():
+                self._publish_event(
+                    QueueLoopNextEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        index=event.index,
+                        node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
+                        output=event.pre_loop_output,
+                    )
+                )
+            case NodeRunLoopSucceededEvent() | NodeRunLoopFailedEvent():
+                self._publish_event(
+                    QueueLoopCompletedEvent(
+                        node_execution_id=event.id,
+                        node_id=event.node_id,
+                        node_type=event.node_type,
+                        node_title=event.node_title,
+                        start_at=event.start_at,
+                        node_run_index=workflow_entry.graph_engine.graph_runtime_state.node_run_steps,
+                        inputs=event.inputs,
+                        outputs=event.outputs,
+                        metadata=event.metadata,
+                        steps=event.steps,
+                        error=event.error if isinstance(event, NodeRunLoopFailedEvent) else None,
+                    )
                 )
-            )
 
     def _enqueue_human_input_notifications(self, reasons: Sequence[object]) -> None:
         for reason in reasons:

api/core/app/entities/queue_entities.py

@@ -11,7 +11,6 @@ from graphon.entities import WorkflowStartReason
 from graphon.entities.pause_reason import PauseReason
 from graphon.enums import NodeType, WorkflowNodeExecutionMetadataKey
 from graphon.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
-from graphon.variables.segments import Segment
 
 
 class QueueEvent(StrEnum):
@@ -509,10 +508,6 @@ class QueueHumanInputFormFilledEvent(AppQueueEvent):
     action_id: str
     action_text: str
 
-    # Keep the field name aligned with Graphon so the app-layer bridge does not
-    # need to translate between two equivalent payload names.
-    submitted_data: Mapping[str, Segment] | None = None
-
 
 class QueueHumanInputFormTimeoutEvent(AppQueueEvent):
     """

api/core/app/entities/task_entities.py

@@ -342,8 +342,6 @@ class HumanInputFormFilledResponse(StreamResponse):
         action_id: str
         action_text: str
 
-        submitted_data: Mapping[str, Any] | None = None
-
     event: StreamEvent = StreamEvent.HUMAN_INPUT_FORM_FILLED
     workflow_run_id: str
     data: Data

api/core/app/file_access/__init__.py

@@ -1,6 +1,13 @@
 from .controller import DatabaseFileAccessController
 from .protocols import FileAccessControllerProtocol
-from .scope import FileAccessScope, bind_file_access_scope, get_current_file_access_scope
+from .scope import (
+    FileAccessScope,
+    bind_file_access_scope,
+    get_current_file_access_scope,
+    grant_retriever_segment_access,
+    grant_upload_file_access,
+    is_retriever_segment_access_granted,
+)
 
 __all__ = [
     "DatabaseFileAccessController",
@@ -8,4 +15,7 @@ __all__ = [
     "FileAccessScope",
     "bind_file_access_scope",
     "get_current_file_access_scope",
+    "grant_retriever_segment_access",
+    "grant_upload_file_access",
+    "is_retriever_segment_access_granted",
 ]

api/core/app/file_access/controller.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from collections.abc import Callable
 
-from sqlalchemy import select
+from sqlalchemy import and_, or_, select
 from sqlalchemy.orm import Session
 from sqlalchemy.sql import Select
 
@@ -18,7 +18,8 @@ class DatabaseFileAccessController(FileAccessControllerProtocol):
 
     Tenant scoping remains mandatory. When the current execution belongs to an
     end user, the lookup is additionally constrained to that end user's file
-    ownership markers.
+    ownership markers, plus upload files explicitly granted by the current
+    execution context.
     """
 
     _scope_getter: Callable[[], FileAccessScope | None]
@@ -47,10 +48,19 @@ class DatabaseFileAccessController(FileAccessControllerProtocol):
         if not resolved_scope.requires_user_ownership:
             return scoped_stmt
 
-        return scoped_stmt.where(
+        user_owned_filter = and_(
             UploadFile.created_by_role == CreatorUserRole.END_USER,
             UploadFile.created_by == resolved_scope.user_id,
         )
+        if not resolved_scope.granted_upload_file_ids:
+            return scoped_stmt.where(user_owned_filter)
+
+        return scoped_stmt.where(
+            or_(
+                user_owned_filter,
+                UploadFile.id.in_(resolved_scope.granted_upload_file_ids),
+            )
+        )
 
     def apply_tool_file_filters(
         self,

api/core/app/file_access/scope.py

@@ -1,9 +1,9 @@
 from __future__ import annotations
 
-from collections.abc import Generator  # Changed from Iterator
+from collections.abc import Generator, Iterable
 from contextlib import contextmanager
 from contextvars import ContextVar
-from dataclasses import dataclass
+from dataclasses import dataclass, field, replace
 
 from core.app.entities.app_invoke_entities import InvokeFrom, UserFrom
 
@@ -15,12 +15,23 @@ _current_file_access_scope: ContextVar[FileAccessScope | None] = ContextVar(
 
 @dataclass(frozen=True, slots=True)
 class FileAccessScope:
-    """Request-scoped ownership context used by workflow-layer file lookups."""
+    """Request-scoped ownership context used by workflow-layer file lookups.
+
+    ``granted_upload_file_ids`` is execution-local: callers may add upload files
+    that were returned by trusted retrieval paths without changing persistent
+    ownership markers.
+
+    ``granted_retriever_segment_ids`` gates lazy attachment loading by segment
+    ID, so user-provided context cannot make a later LLM node load arbitrary
+    same-tenant knowledge attachments.
+    """
 
     tenant_id: str
     user_id: str
     user_from: UserFrom
     invoke_from: InvokeFrom
+    granted_upload_file_ids: frozenset[str] = field(default_factory=frozenset)
+    granted_retriever_segment_ids: frozenset[str] = field(default_factory=frozenset)
 
     @property
     def requires_user_ownership(self) -> bool:
@@ -31,8 +42,49 @@ def get_current_file_access_scope() -> FileAccessScope | None:
     return _current_file_access_scope.get()
 
 
+def grant_upload_file_access(upload_file_ids: Iterable[str]) -> None:
+    scope = _current_file_access_scope.get()
+    if scope is None:
+        return
+
+    granted_upload_file_ids = frozenset(str(file_id) for file_id in upload_file_ids if file_id)
+    if not granted_upload_file_ids:
+        return
+
+    _current_file_access_scope.set(
+        replace(
+            scope,
+            granted_upload_file_ids=scope.granted_upload_file_ids | granted_upload_file_ids,
+        )
+    )
+
+
+def grant_retriever_segment_access(segment_ids: Iterable[str]) -> None:
+    scope = _current_file_access_scope.get()
+    if scope is None:
+        return
+
+    granted_segment_ids = frozenset(str(segment_id) for segment_id in segment_ids if segment_id)
+    if not granted_segment_ids:
+        return
+
+    _current_file_access_scope.set(
+        replace(
+            scope,
+            granted_retriever_segment_ids=scope.granted_retriever_segment_ids | granted_segment_ids,
+        )
+    )
+
+
+def is_retriever_segment_access_granted(segment_id: str) -> bool:
+    scope = _current_file_access_scope.get()
+    if scope is None or not scope.requires_user_ownership:
+        return True
+    return str(segment_id) in scope.granted_retriever_segment_ids
+
+
 @contextmanager
-def bind_file_access_scope(scope: FileAccessScope) -> Generator[None, None, None]:  # Changed from Iterator[None]
+def bind_file_access_scope(scope: FileAccessScope) -> Generator[None, None, None]:
     token = _current_file_access_scope.set(scope)
     try:
         yield

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -140,42 +140,43 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
         :return:
         """
         for stream_response in generator:
-            if isinstance(stream_response, ErrorStreamResponse):
-                raise stream_response.err
-            elif isinstance(stream_response, MessageEndStreamResponse):
-                extras = {"usage": self._task_state.llm_result.usage.model_dump()}
-                if self._task_state.metadata:
-                    extras["metadata"] = self._task_state.metadata.model_dump()
-                response: ChatbotAppBlockingResponse | CompletionAppBlockingResponse
-                if self._conversation_mode == AppMode.COMPLETION:
-                    response = CompletionAppBlockingResponse(
-                        task_id=self._application_generate_entity.task_id,
-                        data=CompletionAppBlockingResponse.Data(
-                            id=self._message_id,
-                            mode=self._conversation_mode,
-                            message_id=self._message_id,
-                            answer=self._task_state.llm_result.message.get_text_content(),
-                            created_at=self._message_created_at,
-                            **extras,
-                        ),
-                    )
-                else:
-                    response = ChatbotAppBlockingResponse(
-                        task_id=self._application_generate_entity.task_id,
-                        data=ChatbotAppBlockingResponse.Data(
-                            id=self._message_id,
-                            mode=self._conversation_mode,
-                            conversation_id=self._conversation_id,
-                            message_id=self._message_id,
-                            answer=self._task_state.llm_result.message.get_text_content(),
-                            created_at=self._message_created_at,
-                            **extras,
-                        ),
-                    )
+            match stream_response:
+                case ErrorStreamResponse():
+                    raise stream_response.err
+                case MessageEndStreamResponse():
+                    extras = {"usage": self._task_state.llm_result.usage.model_dump()}
+                    if self._task_state.metadata:
+                        extras["metadata"] = self._task_state.metadata.model_dump()
+                    response: ChatbotAppBlockingResponse | CompletionAppBlockingResponse
+                    if self._conversation_mode == AppMode.COMPLETION:
+                        response = CompletionAppBlockingResponse(
+                            task_id=self._application_generate_entity.task_id,
+                            data=CompletionAppBlockingResponse.Data(
+                                id=self._message_id,
+                                mode=self._conversation_mode,
+                                message_id=self._message_id,
+                                answer=self._task_state.llm_result.message.get_text_content(),
+                                created_at=self._message_created_at,
+                                **extras,
+                            ),
+                        )
+                    else:
+                        response = ChatbotAppBlockingResponse(
+                            task_id=self._application_generate_entity.task_id,
+                            data=ChatbotAppBlockingResponse.Data(
+                                id=self._message_id,
+                                mode=self._conversation_mode,
+                                conversation_id=self._conversation_id,
+                                message_id=self._message_id,
+                                answer=self._task_state.llm_result.message.get_text_content(),
+                                created_at=self._message_created_at,
+                                **extras,
+                            ),
+                        )
 
-                return response
-            else:
-                continue
+                    return response
+                case _:
+                    continue
 
         raise RuntimeError("queue listening stopped unexpectedly.")
 
@@ -265,104 +266,107 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
                 publisher.publish(message)
             event = message.event
 
-            if isinstance(event, QueueErrorEvent):
-                with sessionmaker(bind=db.engine).begin() as session:
-                    err = self.handle_error(event=event, session=session, message_id=self._message_id)
-                yield self.error_to_stream_response(err)
-                break
-            elif isinstance(event, QueueStopEvent | QueueMessageEndEvent):
-                if isinstance(event, QueueMessageEndEvent):
-                    if event.llm_result:
-                        self._task_state.llm_result = event.llm_result
-                else:
-                    self._handle_stop(event)
+            match event:
+                case QueueErrorEvent():
+                    with sessionmaker(bind=db.engine).begin() as session:
+                        err = self.handle_error(event=event, session=session, message_id=self._message_id)
+                    yield self.error_to_stream_response(err)
+                    break
+                case QueueStopEvent() | QueueMessageEndEvent():
+                    if isinstance(event, QueueMessageEndEvent):
+                        if event.llm_result:
+                            self._task_state.llm_result = event.llm_result
+                    else:
+                        self._handle_stop(event)
 
-                # handle output moderation
-                output_moderation_answer = self.handle_output_moderation_when_task_finished(
-                    self._task_state.llm_result.message.get_text_content()
-                )
-                if output_moderation_answer:
-                    self._task_state.llm_result.message.content = output_moderation_answer
-                    yield self._message_cycle_manager.message_replace_to_stream_response(
-                        answer=output_moderation_answer
+                    # handle output moderation
+                    output_moderation_answer = self.handle_output_moderation_when_task_finished(
+                        self._task_state.llm_result.message.get_text_content()
                     )
-
-                with sessionmaker(bind=db.engine).begin() as session:
-                    # Save message
-                    self._save_message(session=session, trace_manager=trace_manager)
-                message_end_resp = self._message_end_to_stream_response()
-                yield message_end_resp
-            elif isinstance(event, QueueRetrieverResourcesEvent):
-                self._message_cycle_manager.handle_retriever_resources(event)
-            elif isinstance(event, QueueAnnotationReplyEvent):
-                annotation = self._message_cycle_manager.handle_annotation_reply(event)
-                if annotation:
-                    self._task_state.llm_result.message.content = annotation.content
-            elif isinstance(event, QueueAgentThoughtEvent):
-                agent_thought_response = self._agent_thought_to_stream_response(event)
-                if agent_thought_response is not None:
-                    yield agent_thought_response
-            elif isinstance(event, QueueMessageFileEvent):
-                response = self._message_cycle_manager.message_file_to_stream_response(event)
-                if response:
-                    yield response
-            elif isinstance(event, QueueLLMChunkEvent | QueueAgentMessageEvent):
-                chunk = event.chunk
-                delta_text = chunk.delta.message.content
-                if delta_text is None:
-                    continue
-                if isinstance(chunk.delta.message.content, list):
-                    delta_text = ""
-                    for content in chunk.delta.message.content:
-                        logger.debug(
-                            "The content type %s in LLM chunk delta message content.: %r", type(content), content
+                    if output_moderation_answer:
+                        self._task_state.llm_result.message.content = output_moderation_answer
+                        yield self._message_cycle_manager.message_replace_to_stream_response(
+                            answer=output_moderation_answer
                         )
-                        if isinstance(content, TextPromptMessageContent):
-                            delta_text += content.data
-                        elif isinstance(content, str):
-                            delta_text += content  # failback to str
-                        else:
-                            logger.warning(
-                                "Unsupported content type %s in LLM chunk delta message content.: %r",
-                                type(content),
-                                content,
+
+                    with sessionmaker(bind=db.engine).begin() as session:
+                        # Save message
+                        self._save_message(session=session, trace_manager=trace_manager)
+                    message_end_resp = self._message_end_to_stream_response()
+                    yield message_end_resp
+                case QueueRetrieverResourcesEvent():
+                    self._message_cycle_manager.handle_retriever_resources(event)
+                case QueueAnnotationReplyEvent():
+                    annotation = self._message_cycle_manager.handle_annotation_reply(event)
+                    if annotation:
+                        self._task_state.llm_result.message.content = annotation.content
+                case QueueAgentThoughtEvent():
+                    agent_thought_response = self._agent_thought_to_stream_response(event)
+                    if agent_thought_response is not None:
+                        yield agent_thought_response
+                case QueueMessageFileEvent():
+                    response = self._message_cycle_manager.message_file_to_stream_response(event)
+                    if response:
+                        yield response
+                case QueueLLMChunkEvent() | QueueAgentMessageEvent():
+                    chunk = event.chunk
+                    delta_text = chunk.delta.message.content
+                    if delta_text is None:
+                        continue
+                    if isinstance(chunk.delta.message.content, list):
+                        delta_text = ""
+                        for content in chunk.delta.message.content:
+                            logger.debug(
+                                "The content type %s in LLM chunk delta message content.: %r", type(content), content
                             )
-                            continue
+                            match content:
+                                case TextPromptMessageContent():
+                                    delta_text += content.data
+                                case str():
+                                    delta_text += content  # failback to str
+                                case _:
+                                    logger.warning(
+                                        "Unsupported content type %s in LLM chunk delta message content.: %r",
+                                        type(content),
+                                        content,
+                                    )
+                                    continue
 
-                if not self._task_state.llm_result.prompt_messages:
-                    self._task_state.llm_result.prompt_messages = chunk.prompt_messages
+                    if not self._task_state.llm_result.prompt_messages:
+                        self._task_state.llm_result.prompt_messages = chunk.prompt_messages
 
-                # handle output moderation chunk
-                should_direct_answer = self._handle_output_moderation_chunk(cast(str, delta_text))
-                if should_direct_answer:
+                    # handle output moderation chunk
+                    should_direct_answer = self._handle_output_moderation_chunk(cast(str, delta_text))
+                    if should_direct_answer:
+                        continue
+
+                    current_content = cast(str, self._task_state.llm_result.message.content)
+                    current_content += cast(str, delta_text)
+                    self._task_state.llm_result.message.content = current_content
+
+                    match event:
+                        case QueueLLMChunkEvent():
+                            # Determine the event type once, on first LLM chunk, and reuse for subsequent chunks
+                            if not hasattr(self, "_precomputed_event_type") or self._precomputed_event_type is None:
+                                self._precomputed_event_type = self._message_cycle_manager.get_message_event_type(
+                                    message_id=self._message_id
+                                )
+                            yield self._message_cycle_manager.message_to_stream_response(
+                                answer=cast(str, delta_text),
+                                message_id=self._message_id,
+                                event_type=self._precomputed_event_type,
+                            )
+                        case _:
+                            yield self._agent_message_to_stream_response(
+                                answer=cast(str, delta_text),
+                                message_id=self._message_id,
+                            )
+                case QueueMessageReplaceEvent():
+                    yield self._message_cycle_manager.message_replace_to_stream_response(answer=event.text)
+                case QueuePingEvent():
+                    yield self.ping_stream_response()
+                case _:
                     continue
-
-                current_content = cast(str, self._task_state.llm_result.message.content)
-                current_content += cast(str, delta_text)
-                self._task_state.llm_result.message.content = current_content
-
-                if isinstance(event, QueueLLMChunkEvent):
-                    # Determine the event type once, on first LLM chunk, and reuse for subsequent chunks
-                    if not hasattr(self, "_precomputed_event_type") or self._precomputed_event_type is None:
-                        self._precomputed_event_type = self._message_cycle_manager.get_message_event_type(
-                            message_id=self._message_id
-                        )
-                    yield self._message_cycle_manager.message_to_stream_response(
-                        answer=cast(str, delta_text),
-                        message_id=self._message_id,
-                        event_type=self._precomputed_event_type,
-                    )
-                else:
-                    yield self._agent_message_to_stream_response(
-                        answer=cast(str, delta_text),
-                        message_id=self._message_id,
-                    )
-            elif isinstance(event, QueueMessageReplaceEvent):
-                yield self._message_cycle_manager.message_replace_to_stream_response(answer=event.text)
-            elif isinstance(event, QueuePingEvent):
-                yield self.ping_stream_response()
-            else:
-                continue
         if publisher:
             publisher.publish(None)
         if self._conversation_name_generate_thread:

api/core/base/tts/app_generator_tts_publisher.py

@@ -95,13 +95,14 @@ class AppGeneratorTTSPublisher:
                     message_content = message.event.chunk.delta.message.content
                     if not message_content:
                         continue
-                    if isinstance(message_content, str):
-                        self.msg_text += message_content
-                    elif isinstance(message_content, list):
-                        for content in message_content:
-                            if not isinstance(content, TextPromptMessageContent):
-                                continue
-                            self.msg_text += content.data
+                    match message_content:
+                        case str():
+                            self.msg_text += message_content
+                        case list():
+                            for content in message_content:
+                                if not isinstance(content, TextPromptMessageContent):
+                                    continue
+                                self.msg_text += content.data
                 elif isinstance(message.event, QueueTextChunkEvent):
                     self.msg_text += message.event.text
                 elif isinstance(message.event, QueueNodeSucceededEvent):

api/core/entities/execution_extra_content.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 from collections.abc import Mapping, Sequence
 from typing import Any, TypeAlias
 
-from pydantic import BaseModel, ConfigDict, Field, JsonValue
+from pydantic import BaseModel, ConfigDict, Field
 
 from graphon.nodes.human_input.entities import FormInputConfig, UserActionConfig
 from models.execution_extra_content import ExecutionContentType
@@ -19,8 +19,6 @@ class HumanInputFormDefinition(BaseModel):
     inputs: Sequence[FormInputConfig] = Field(default_factory=list)
     actions: Sequence[UserActionConfig] = Field(default_factory=list)
     display_in_ui: bool = False
-
-    # `form_token` is `None` if the corresponding form has been submitted.
     form_token: str | None = None
     resolved_default_values: Mapping[str, Any] = Field(default_factory=dict)
     expiration_time: int
@@ -31,31 +29,16 @@ class HumanInputFormSubmissionData(BaseModel):
 
     node_id: str
     node_title: str
-
-    # deprecate: the rendered_content is deprecated and only for historical reasons.
     rendered_content: str
-
-    # The identifier of action user has chosen.
     action_id: str
-    # The button text of the action user has chosen.
     action_text: str
 
-    # submitted_data records the submitted form data.
-    # Keys correspond to `output_variable_name` of HumanInput inputs.
-    # Values are serialized JSON forms of runtime values, including file dictionaries.
-    #
-    # For form submitted before this field is introduced, this field is populated from
-    # the stored submission data.
-    submitted_data: Mapping[str, JsonValue] | None = None
-
 
 class HumanInputContent(BaseModel):
     model_config = ConfigDict(frozen=True)
 
     workflow_run_id: str
     submitted: bool
-    # Both the form_defintion and the form_submission_data are present in
-    # HumanInputContent. For historical records, the
     form_definition: HumanInputFormDefinition | None = None
     form_submission_data: HumanInputFormSubmissionData | None = None
     type: ExecutionContentType = Field(default=ExecutionContentType.HUMAN_INPUT)

api/core/entities/provider_configuration.py

@@ -171,9 +171,9 @@ class ProviderConfiguration(BaseModel):
                 current_credential_id = self.custom_configuration.provider.current_credential_id
 
             if current_credential_id:
-                from core.helper.credential_utils import check_credential_policy_compliance
+                from core.helper.credential_utils import runtime_check_credential_policy_compliance
 
-                check_credential_policy_compliance(
+                runtime_check_credential_policy_compliance(
                     credential_id=current_credential_id,
                     provider=self.provider.provider,
                     credential_type=PluginCredentialType.MODEL,
@@ -182,9 +182,9 @@ class ProviderConfiguration(BaseModel):
                 # no current credential id, check all available credentials
                 if self.custom_configuration.provider:
                     for credential_configuration in self.custom_configuration.provider.available_credentials:
-                        from core.helper.credential_utils import check_credential_policy_compliance
+                        from core.helper.credential_utils import runtime_check_credential_policy_compliance
 
-                        check_credential_policy_compliance(
+                        runtime_check_credential_policy_compliance(
                             credential_id=credential_configuration.credential_id,
                             provider=self.provider.provider,
                             credential_type=PluginCredentialType.MODEL,

api/core/errors/error.py

@@ -1,9 +1,9 @@
 class LLMError(ValueError):
     """Base class for all LLM exceptions."""
 
-    description: str | None = None
+    description: str = ""
 
-    def __init__(self, description: str | None = None):
+    def __init__(self, description: str = ""):
         self.description = description
 
 

api/core/evaluation/base_evaluation_instance.py

@@ -1,279 +0,0 @@
-import logging
-from abc import ABC, abstractmethod
-from collections.abc import Mapping
-from typing import Any
-
-from core.evaluation.entities.evaluation_entity import (
-    CustomizedMetrics,
-    EvaluationCategory,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    EvaluationMetric,
-    NodeInfo,
-)
-from graphon.node_events.base import NodeRunResult
-
-logger = logging.getLogger(__name__)
-
-
-class BaseEvaluationInstance(ABC):
-    """Abstract base class for evaluation framework adapters."""
-
-    @abstractmethod
-    def evaluate_llm(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        """Evaluate LLM outputs using the configured framework."""
-        ...
-
-    @abstractmethod
-    def evaluate_retrieval(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        """Evaluate retrieval quality using the configured framework."""
-        ...
-
-    @abstractmethod
-    def evaluate_agent(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        """Evaluate agent outputs using the configured framework."""
-        ...
-
-    @abstractmethod
-    def get_supported_metrics(self, category: EvaluationCategory) -> list[str]:
-        """Return the list of supported metric names for a given evaluation category."""
-        ...
-
-    def evaluate_with_customized_workflow(
-        self,
-        node_run_result_mapping_list: list[dict[str, NodeRunResult]],
-        customized_metrics: CustomizedMetrics,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        """Evaluate using a published workflow as the evaluator.
-
-        The evaluator workflow's output variables are treated as metrics:
-        each output variable name becomes a metric name, and its value
-        becomes the score.
-
-        Args:
-            node_run_result_mapping_list: One mapping per test-data item,
-                where each mapping is ``{node_id: NodeRunResult}`` from the
-                target execution.
-            customized_metrics: Contains ``evaluation_workflow_id`` (the
-                published evaluator workflow) and ``input_fields`` (value
-                sources for the evaluator's input variables).
-            tenant_id: Tenant scope.
-
-        Returns:
-            A list of ``EvaluationItemResult`` with metrics extracted from
-            the evaluator workflow's output variables.
-        """
-        from sqlalchemy.orm import Session
-
-        from core.app.apps.workflow.app_generator import WorkflowAppGenerator
-        from core.app.entities.app_invoke_entities import InvokeFrom
-        from core.evaluation.runners import get_service_account_for_app
-        from models.engine import db
-        from models.model import App
-        from services.workflow_service import WorkflowService
-
-        workflow_id = customized_metrics.evaluation_workflow_id
-        if not workflow_id:
-            raise ValueError("customized_metrics must contain 'evaluation_workflow_id' for customized evaluator")
-
-        # Load the evaluator workflow resources using a dedicated session
-        with Session(db.engine, expire_on_commit=False) as session, session.begin():
-            app = session.query(App).filter_by(id=workflow_id, tenant_id=tenant_id).first()
-            if not app:
-                raise ValueError(f"Evaluation workflow app {workflow_id} not found in tenant {tenant_id}")
-            service_account = get_service_account_for_app(session, workflow_id)
-
-        workflow_service = WorkflowService()
-        published_workflow = workflow_service.get_published_workflow(app_model=app)
-        if not published_workflow:
-            raise ValueError(f"No published workflow found for evaluation app {workflow_id}")
-
-        eval_results: list[EvaluationItemResult] = []
-        for idx, node_run_result_mapping in enumerate(node_run_result_mapping_list):
-            try:
-                workflow_inputs = self._build_workflow_inputs(
-                    customized_metrics.input_fields,
-                    node_run_result_mapping,
-                )
-
-                generator = WorkflowAppGenerator()
-                response: Mapping[str, Any] = generator.generate(
-                    app_model=app,
-                    workflow=published_workflow,
-                    user=service_account,
-                    args={"inputs": workflow_inputs},
-                    invoke_from=InvokeFrom.SERVICE_API,
-                    streaming=False,
-                    call_depth=0,
-                )
-
-                metrics = self._extract_workflow_metrics(response, workflow_id)
-                eval_results.append(
-                    EvaluationItemResult(
-                        index=idx,
-                        metrics=metrics,
-                    )
-                )
-            except Exception:
-                logger.exception(
-                    "Customized evaluator failed for item %d with workflow %s",
-                    idx,
-                    workflow_id,
-                )
-                eval_results.append(EvaluationItemResult(index=idx))
-
-        return eval_results
-
-    @staticmethod
-    def _build_workflow_inputs(
-        input_fields: dict[str, Any],
-        node_run_result_mapping: dict[str, NodeRunResult],
-    ) -> dict[str, Any]:
-        """Build customized workflow inputs by resolving value sources.
-
-        Each entry in ``input_fields`` maps a workflow input variable name
-        to its value source, which can be:
-
-          - **Constant**: a plain string without ``{{#…#}}`` used as-is.
-          - **Expression**: a string containing one or more
-            ``{{#node_id.output_key#}}`` selectors (same format as
-            ``VariableTemplateParser``) resolved from
-            ``node_run_result_mapping``.
-
-        """
-        from graphon.nodes.base.variable_template_parser import REGEX as VARIABLE_REGEX
-
-        workflow_inputs: dict[str, Any] = {}
-
-        for field_name, value_source in input_fields.items():
-            if not isinstance(value_source, str):
-                # Non-string values (numbers, bools, dicts) are used directly.
-                workflow_inputs[field_name] = value_source
-                continue
-
-            # Check if the entire value is a single expression.
-            full_match = VARIABLE_REGEX.fullmatch(value_source)
-            if full_match:
-                workflow_inputs[field_name] = resolve_variable_selector(
-                    full_match.group(1),
-                    node_run_result_mapping,
-                )
-            elif VARIABLE_REGEX.search(value_source):
-                # Mixed template: interpolate all expressions as strings.
-                workflow_inputs[field_name] = VARIABLE_REGEX.sub(
-                    lambda m: str(resolve_variable_selector(m.group(1), node_run_result_mapping)),
-                    value_source,
-                )
-            else:
-                # Plain constant — no expression markers.
-                workflow_inputs[field_name] = value_source
-
-        return workflow_inputs
-
-    @staticmethod
-    def _extract_workflow_metrics(
-        response: Mapping[str, object],
-        evaluation_workflow_id: str,
-    ) -> list[EvaluationMetric]:
-        """Extract evaluation metrics from workflow output variables.
-
-        Each metric's ``node_info`` is set with *evaluation_workflow_id* as
-        the ``node_id``, so that judgment conditions can reference customized
-        metrics via ``variable_selector: [evaluation_workflow_id, metric_name]``.
-        """
-        metrics: list[EvaluationMetric] = []
-        node_info = NodeInfo(node_id=evaluation_workflow_id, type="customized", title="customized")
-
-        data = response.get("data")
-        if not isinstance(data, Mapping):
-            logger.warning("Unexpected workflow response format: missing 'data' dict")
-            return metrics
-
-        outputs = data.get("outputs")
-        if not isinstance(outputs, dict):
-            logger.warning("Unexpected workflow response format: 'outputs' is not a dict")
-            return metrics
-
-        for key, raw_value in outputs.items():
-            if not isinstance(key, str):
-                continue
-            metrics.append(EvaluationMetric(name=key, value=raw_value, node_info=node_info))
-
-        return metrics
-
-
-def resolve_variable_selector(
-    selector_raw: str,
-    node_run_result_mapping: dict[str, NodeRunResult],
-) -> object:
-    """
-    Resolve a ``#node_id.output_key#`` selector against node run results.
-    """
-    #
-    cleaned = selector_raw.strip("#")
-    parts = cleaned.split(".")
-
-    if len(parts) < 2:
-        logger.warning(
-            "Selector '%s' must have at least node_id.output_key",
-            selector_raw,
-        )
-        return ""
-
-    node_id = parts[0]
-    output_path = parts[1:]
-
-    node_result = node_run_result_mapping.get(node_id)
-    if not node_result or not node_result.outputs:
-        logger.warning(
-            "Selector '%s': node '%s' not found or has no outputs",
-            selector_raw,
-            node_id,
-        )
-        return ""
-
-    # Traverse the output path to support nested keys.
-    current: object = node_result.outputs
-    for key in output_path:
-        if isinstance(current, Mapping):
-            next_val = current.get(key)
-            if next_val is None:
-                logger.warning(
-                    "Selector '%s': key '%s' not found in node '%s' outputs",
-                    selector_raw,
-                    key,
-                    node_id,
-                )
-                return ""
-            current = next_val
-        else:
-            logger.warning(
-                "Selector '%s': cannot traverse into non-dict value at key '%s'",
-                selector_raw,
-                key,
-            )
-            return ""
-
-    return current if current is not None else ""

api/core/evaluation/entities/config_entity.py

@@ -1,27 +0,0 @@
-from enum import StrEnum
-
-from pydantic import BaseModel
-
-
-class EvaluationFrameworkEnum(StrEnum):
-    RAGAS = "ragas"
-    DEEPEVAL = "deepeval"
-    NONE = "none"
-
-
-class BaseEvaluationConfig(BaseModel):
-    """Base configuration for evaluation frameworks."""
-
-    pass
-
-
-class RagasConfig(BaseEvaluationConfig):
-    """RAGAS-specific configuration."""
-
-    pass
-
-
-class DeepEvalConfig(BaseEvaluationConfig):
-    """DeepEval-specific configuration."""
-
-    pass

api/core/evaluation/entities/evaluation_entity.py

@@ -1,280 +0,0 @@
-import json
-from enum import StrEnum
-from typing import Any
-
-from pydantic import BaseModel, Field
-
-from core.evaluation.entities.judgment_entity import JudgmentConfig, JudgmentResult
-
-
-class EvaluationCategory(StrEnum):
-    LLM = "llm"
-    RETRIEVAL = "knowledge_retrieval"
-    AGENT = "agent"
-    WORKFLOW = "workflow"
-    SNIPPET = "snippet"
-    KNOWLEDGE_BASE = "knowledge_base"
-
-
-class EvaluationMetricName(StrEnum):
-    """Canonical metric names shared across all evaluation frameworks.
-
-    Each framework maps these names to its own internal implementation.
-    A framework that does not support a given metric should log a warning
-    and skip it rather than raising an error.
-
-    ── LLM / general text-quality metrics ──────────────────────────────────
-    FAITHFULNESS
-        Measures whether every claim in the model's response is grounded in
-        the provided retrieved context. A high score means the answer
-        contains no hallucinated content — each statement can be traced back
-        to a passage in the context.
-        Required fields: user_input, response, retrieved_contexts.
-
-    ANSWER_RELEVANCY
-        Measures how well the model's response addresses the user's question.
-        A high score means the answer stays on-topic; a low score indicates
-        irrelevant content or a failure to answer the actual question.
-        Required fields: user_input, response.
-
-    ANSWER_CORRECTNESS
-        Measures the factual accuracy and completeness of the model's answer
-        relative to a ground-truth reference. It combines semantic similarity
-        with key-fact coverage, so both meaning and content matter.
-        Required fields: user_input, response, reference (expected_output).
-
-    SEMANTIC_SIMILARITY
-        Measures the cosine similarity between the model's response and the
-        reference answer in an embedding space. It evaluates whether the two
-        texts convey the same meaning, independent of factual correctness.
-        Required fields: response, reference (expected_output).
-
-    ── Retrieval-quality metrics ────────────────────────────────────────────
-    CONTEXT_PRECISION
-        Measures the proportion of retrieved context chunks that are actually
-        relevant to the question (precision). A high score means the retrieval
-        pipeline returns little noise.
-        Required fields: user_input, reference, retrieved_contexts.
-
-    CONTEXT_RECALL
-        Measures the proportion of ground-truth information that is covered by
-        the retrieved context chunks (recall). A high score means the retrieval
-        pipeline does not miss important supporting evidence.
-        Required fields: user_input, reference, retrieved_contexts.
-
-    CONTEXT_RELEVANCE
-        Measures how relevant each individual retrieved chunk is to the query.
-        Similar to CONTEXT_PRECISION but evaluated at the chunk level rather
-        than against a reference answer.
-        Required fields: user_input, retrieved_contexts.
-
-    ── Agent-quality metrics ────────────────────────────────────────────────
-    TOOL_CORRECTNESS
-        Measures the correctness of the tool calls made by the agent during
-        task execution — both the choice of tool and the arguments passed.
-        A high score means the agent's tool-use strategy matches the expected
-        behavior.
-        Required fields: actual tool calls vs. expected tool calls.
-
-    TASK_COMPLETION
-        Measures whether the agent ultimately achieves the user's stated goal.
-        It evaluates the reasoning chain, intermediate steps, and final output
-        holistically; a high score means the task was fully accomplished.
-        Required fields: user_input, actual_output.
-    """
-
-    # LLM / general text-quality metrics
-    FAITHFULNESS = "faithfulness"
-    ANSWER_RELEVANCY = "answer_relevancy"
-    ANSWER_CORRECTNESS = "answer_correctness"
-    SEMANTIC_SIMILARITY = "semantic_similarity"
-
-    # Retrieval-quality metrics
-    CONTEXT_PRECISION = "context_precision"
-    CONTEXT_RECALL = "context_recall"
-    CONTEXT_RELEVANCE = "context_relevance"
-
-    # Agent-quality metrics
-    TOOL_CORRECTNESS = "tool_correctness"
-    TASK_COMPLETION = "task_completion"
-
-
-# Per-category canonical metric lists used by get_supported_metrics().
-LLM_METRIC_NAMES: list[EvaluationMetricName] = [
-    EvaluationMetricName.FAITHFULNESS,        # Every claim is grounded in context; no hallucinations
-    EvaluationMetricName.ANSWER_RELEVANCY,    # Response stays on-topic and addresses the question
-    EvaluationMetricName.ANSWER_CORRECTNESS,  # Factual accuracy and completeness vs. reference
-    EvaluationMetricName.SEMANTIC_SIMILARITY,  # Semantic closeness to the reference answer
-]
-
-RETRIEVAL_METRIC_NAMES: list[EvaluationMetricName] = [
-    EvaluationMetricName.CONTEXT_PRECISION,  # Fraction of retrieved chunks that are relevant (precision)
-    EvaluationMetricName.CONTEXT_RECALL,     # Fraction of ground-truth info covered by retrieval (recall)
-    EvaluationMetricName.CONTEXT_RELEVANCE,  # Per-chunk relevance to the query
-]
-
-AGENT_METRIC_NAMES: list[EvaluationMetricName] = [
-    EvaluationMetricName.TOOL_CORRECTNESS,  # Correct tool selection and arguments
-    EvaluationMetricName.TASK_COMPLETION,   # Whether the agent fully achieves the user's goal
-]
-
-WORKFLOW_METRIC_NAMES: list[EvaluationMetricName] = [
-    EvaluationMetricName.FAITHFULNESS,
-    EvaluationMetricName.ANSWER_RELEVANCY,
-    EvaluationMetricName.ANSWER_CORRECTNESS,
-]
-
-METRIC_NODE_TYPE_MAPPING: dict[str, str] = {
-    **{m.value: "llm" for m in LLM_METRIC_NAMES},
-    **{m.value: "knowledge-retrieval" for m in RETRIEVAL_METRIC_NAMES},
-    **{m.value: "agent" for m in AGENT_METRIC_NAMES},
-}
-
-METRIC_VALUE_TYPE_MAPPING: dict[str, str] = {
-    EvaluationMetricName.FAITHFULNESS: "number",
-    EvaluationMetricName.ANSWER_RELEVANCY: "number",
-    EvaluationMetricName.ANSWER_CORRECTNESS: "number",
-    EvaluationMetricName.SEMANTIC_SIMILARITY: "number",
-    EvaluationMetricName.CONTEXT_PRECISION: "number",
-    EvaluationMetricName.CONTEXT_RECALL: "number",
-    EvaluationMetricName.CONTEXT_RELEVANCE: "number",
-    EvaluationMetricName.TOOL_CORRECTNESS: "number",
-    EvaluationMetricName.TASK_COMPLETION: "number",
-}
-
-
-class NodeInfo(BaseModel):
-    node_id: str
-    type: str
-    title: str
-
-
-class EvaluationMetric(BaseModel):
-    name: str
-    value: Any
-    details: dict[str, Any] = Field(default_factory=dict)
-    node_info: NodeInfo | None = None
-
-
-class EvaluationItemInput(BaseModel):
-    index: int
-    inputs: dict[str, Any]
-    output: str
-    expected_output: str | None = None
-    context: list[str] | None = None
-
-
-class EvaluationDatasetInput(BaseModel):
-    """Parsed dataset row used throughout evaluation execution.
-
-    ``expected_output`` keeps backward compatibility with the original
-    single-reference template. When users upload node-specific reference
-    columns such as ``LLM 1 : expected_output``, they are stored in
-    ``expected_outputs`` and resolved by node title at execution time.
-    """
-
-    index: int
-    inputs: dict[str, Any]
-    expected_output: str | None = None
-    expected_outputs: dict[str, str] = Field(default_factory=dict)
-
-    def get_expected_output_for_node(self, node_title: str | None) -> str | None:
-        """Return the best matching reference answer for the given node title."""
-        if node_title:
-            if node_title in self.expected_outputs:
-                return self.expected_outputs[node_title]
-
-        if self.expected_output is not None:
-            return self.expected_output
-
-        if len(self.expected_outputs) == 1:
-            return next(iter(self.expected_outputs.values()))
-
-        return None
-
-    def serialize_expected_output(self) -> str | None:
-        """Serialize references for persistence and API responses.
-
-        Single-reference datasets stay unchanged, while multi-node references
-        are stored as JSON so history/detail APIs can still expose the full
-        uploaded payload without changing the database schema.
-        """
-        if self.expected_output is not None and not self.expected_outputs:
-            return self.expected_output
-
-        if not self.expected_outputs:
-            return None
-
-        serialized_expected_outputs = dict(self.expected_outputs)
-        if self.expected_output is not None:
-            serialized_expected_outputs = {"expected_output": self.expected_output, **serialized_expected_outputs}
-
-        return json.dumps(serialized_expected_outputs, ensure_ascii=False, sort_keys=True)
-
-    def iter_expected_output_columns(self) -> list[tuple[str, str]]:
-        """Return uploaded expected-output columns in display order."""
-        columns: list[tuple[str, str]] = []
-        if self.expected_output is not None:
-            columns.append(("expected_output", self.expected_output))
-
-        for node_title, value in self.expected_outputs.items():
-            columns.append((f"{node_title} : expected_output", value))
-
-        return columns
-
-
-class EvaluationItemResult(BaseModel):
-    index: int
-    actual_output: str | None = None
-    metrics: list[EvaluationMetric] = Field(default_factory=list)
-    metadata: dict[str, Any] = Field(default_factory=dict)
-    judgment: JudgmentResult = Field(default_factory=JudgmentResult)
-    error: str | None = None
-
-
-class DefaultMetric(BaseModel):
-    metric: str
-    value_type: str = ""
-    node_info_list: list[NodeInfo]
-
-
-class CustomizedMetricOutputField(BaseModel):
-    variable: str
-    value_type: str
-
-
-class CustomizedMetrics(BaseModel):
-    evaluation_workflow_id: str
-    input_fields: dict[str, Any]
-    output_fields: list[CustomizedMetricOutputField]
-
-
-class EvaluationConfigData(BaseModel):
-    """Structured data for saving evaluation configuration."""
-
-    evaluation_model: str = ""
-    evaluation_model_provider: str = ""
-    default_metrics: list[DefaultMetric] = Field(default_factory=list)
-    customized_metrics: CustomizedMetrics | None = None
-    judgment_config: JudgmentConfig | None = None
-
-
-class EvaluationRunRequest(EvaluationConfigData):
-    """Request body for starting an evaluation run."""
-
-    file_id: str
-
-
-class EvaluationRunData(BaseModel):
-    """Serializable data for Celery task."""
-
-    evaluation_run_id: str
-    tenant_id: str
-    target_type: str
-    target_id: str
-    evaluation_model_provider: str
-    evaluation_model: str
-    default_metrics: list[DefaultMetric] = Field(default_factory=list)
-    customized_metrics: CustomizedMetrics | None = None
-    judgment_config: JudgmentConfig | None = None
-    input_list: list[EvaluationDatasetInput]

api/core/evaluation/entities/judgment_entity.py

@@ -1,118 +0,0 @@
-"""Judgment condition entities for evaluation metric assessment.
-
-Condition structure mirrors the workflow if-else ``Condition`` model from
-``graphon.utils.condition.entities``.  The left-hand side uses
-``variable_selector`` — a two-element list ``[node_id, metric_name]`` — to
-uniquely identify an evaluation metric (different nodes may produce metrics
-with the same name).
-
-Operators reuse ``SupportedComparisonOperator`` from the workflow engine so
-that type semantics stay consistent across the platform.
-
-Typical usage::
-
-    judgment_config = JudgmentConfig(
-        logical_operator="and",
-        conditions=[
-            JudgmentCondition(
-                variable_selector=["node_abc", "faithfulness"],
-                comparison_operator=">",
-                value="0.8",
-            )
-        ],
-    )
-"""
-
-from collections.abc import Sequence
-from typing import Any, Literal
-
-from pydantic import BaseModel, Field, field_validator
-
-from graphon.utils.condition.entities import SupportedComparisonOperator
-
-COMPARISON_OPERATOR_ALIASES: dict[str, str] = {
-    "==": "=",
-    "!=": "≠",
-    ">=": "≥",
-    "<=": "≤",
-    "is null": "null",
-    "is not null": "not null",
-}
-
-
-class JudgmentCondition(BaseModel):
-    """A single judgment condition that checks one metric value.
-
-    Mirrors ``graphon.utils.condition.entities.Condition`` with the left-hand
-    side being a metric selector instead of a workflow variable selector.
-
-    Attributes:
-        variable_selector: ``[node_id, metric_name]`` identifying the metric.
-        comparison_operator: Reuses workflow's ``SupportedComparisonOperator``.
-        value: The comparison target (right side).  For unary operators such
-            as ``empty`` or ``null`` this can be ``None``.
-    """
-
-    variable_selector: list[str]
-    comparison_operator: SupportedComparisonOperator
-    value: str | Sequence[str] | bool | None = None
-
-    @field_validator("comparison_operator", mode="before")
-    @classmethod
-    def normalize_comparison_operator(cls, value: Any) -> Any:
-        """Accept common ASCII/API aliases for workflow comparison operators."""
-        if not isinstance(value, str):
-            return value
-
-        normalized_value = value.strip().lower()
-        alias = COMPARISON_OPERATOR_ALIASES.get(normalized_value)
-        if alias is not None:
-            return alias
-        return value.strip()
-
-
-class JudgmentConfig(BaseModel):
-    """A group of judgment conditions combined with a logical operator.
-
-    Attributes:
-        logical_operator: How to combine condition results — "and" requires
-            all conditions to pass, "or" requires at least one.
-        conditions: The list of individual conditions to evaluate.
-    """
-
-    logical_operator: Literal["and", "or"] = "and"
-    conditions: list[JudgmentCondition] = Field(default_factory=list)
-
-
-class JudgmentConditionResult(BaseModel):
-    """Result of evaluating a single judgment condition.
-
-    Attributes:
-        variable_selector: ``[node_id, metric_name]`` that was checked.
-        comparison_operator: The operator that was applied.
-        expected_value: The resolved comparison value.
-        actual_value: The actual metric value that was evaluated.
-        passed: Whether this individual condition passed.
-        error: Error message if the condition evaluation failed.
-    """
-
-    variable_selector: list[str]
-    comparison_operator: str
-    expected_value: Any = None
-    actual_value: Any = None
-    passed: bool = False
-    error: str | None = None
-
-
-class JudgmentResult(BaseModel):
-    """Overall result of evaluating all judgment conditions for one item.
-
-    Attributes:
-        passed: Whether the overall judgment passed (based on logical_operator).
-        logical_operator: The logical operator used to combine conditions.
-        condition_results: Detailed result for each individual condition.
-    """
-
-    passed: bool = False
-    logical_operator: Literal["and", "or"] = "and"
-    condition_results: list[JudgmentConditionResult] = Field(default_factory=list)

api/core/evaluation/evaluation_manager.py

@@ -1,61 +0,0 @@
-import collections
-import logging
-from typing import Any
-
-from configs import dify_config
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.config_entity import EvaluationFrameworkEnum
-from core.evaluation.entities.evaluation_entity import EvaluationCategory
-
-logger = logging.getLogger(__name__)
-
-
-class EvaluationFrameworkConfigMap(collections.UserDict[str, dict[str, Any]]):
-    """Registry mapping framework enum -> {config_class, evaluator_class}."""
-
-    def __getitem__(self, framework: str) -> dict[str, Any]:
-        match framework:
-            case EvaluationFrameworkEnum.RAGAS:
-                from core.evaluation.entities.config_entity import RagasConfig
-                from core.evaluation.frameworks.ragas.ragas_evaluator import RagasEvaluator
-
-                return {
-                    "config_class": RagasConfig,
-                    "evaluator_class": RagasEvaluator,
-                }
-            case EvaluationFrameworkEnum.DEEPEVAL:
-                raise NotImplementedError("DeepEval adapter is not yet implemented.")
-            case _:
-                raise ValueError(f"Unknown evaluation framework: {framework}")
-
-
-evaluation_framework_config_map = EvaluationFrameworkConfigMap()
-
-
-class EvaluationManager:
-    """Factory for evaluation instances based on global configuration."""
-
-    @staticmethod
-    def get_evaluation_instance() -> BaseEvaluationInstance | None:
-        """Create and return an evaluation instance based on EVALUATION_FRAMEWORK env var."""
-        framework = dify_config.EVALUATION_FRAMEWORK
-        if not framework or framework == EvaluationFrameworkEnum.NONE:
-            return None
-
-        try:
-            config_map = evaluation_framework_config_map[framework]
-            evaluator_class = config_map["evaluator_class"]
-            config_class = config_map["config_class"]
-            config = config_class()
-            return evaluator_class(config)
-        except Exception:
-            logger.exception("Failed to create evaluation instance for framework: %s", framework)
-            return None
-
-    @staticmethod
-    def get_supported_metrics(category: EvaluationCategory) -> list[str]:
-        """Return supported metrics for the current framework and given category."""
-        instance = EvaluationManager.get_evaluation_instance()
-        if instance is None:
-            return []
-        return instance.get_supported_metrics(category)

api/core/evaluation/frameworks/deepeval/deepeval_evaluator.py

@@ -1,299 +0,0 @@
-import logging
-from typing import Any
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.config_entity import DeepEvalConfig
-from core.evaluation.entities.evaluation_entity import (
-    AGENT_METRIC_NAMES,
-    LLM_METRIC_NAMES,
-    RETRIEVAL_METRIC_NAMES,
-    WORKFLOW_METRIC_NAMES,
-    EvaluationCategory,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    EvaluationMetric,
-    EvaluationMetricName,
-)
-from core.evaluation.frameworks.ragas.ragas_model_wrapper import DifyModelWrapper
-
-logger = logging.getLogger(__name__)
-
-# Maps canonical EvaluationMetricName to the corresponding deepeval metric class name.
-# deepeval metric field requirements (LLMTestCase fields):
-#   - faithfulness:       input, actual_output, retrieval_context
-#   - answer_relevancy:   input, actual_output
-#   - context_precision:  input, actual_output, expected_output, retrieval_context
-#   - context_recall:     input, actual_output, expected_output, retrieval_context
-#   - context_relevance:  input, actual_output, retrieval_context
-#   - tool_correctness:   input, actual_output, expected_tools
-#   - task_completion:    input, actual_output
-# Metrics not listed here are unsupported by deepeval and will be skipped.
-_DEEPEVAL_METRIC_MAP: dict[EvaluationMetricName, str] = {
-    EvaluationMetricName.FAITHFULNESS: "FaithfulnessMetric",
-    EvaluationMetricName.ANSWER_RELEVANCY: "AnswerRelevancyMetric",
-    EvaluationMetricName.CONTEXT_PRECISION: "ContextualPrecisionMetric",
-    EvaluationMetricName.CONTEXT_RECALL: "ContextualRecallMetric",
-    EvaluationMetricName.CONTEXT_RELEVANCE: "ContextualRelevancyMetric",
-    EvaluationMetricName.TOOL_CORRECTNESS: "ToolCorrectnessMetric",
-    EvaluationMetricName.TASK_COMPLETION: "TaskCompletionMetric",
-}
-
-
-class DeepEvalEvaluator(BaseEvaluationInstance):
-    """DeepEval framework adapter for evaluation."""
-
-    def __init__(self, config: DeepEvalConfig):
-        self.config = config
-
-    def get_supported_metrics(self, category: EvaluationCategory) -> list[str]:
-        match category:
-            case EvaluationCategory.LLM:
-                candidates = LLM_METRIC_NAMES
-            case EvaluationCategory.RETRIEVAL:
-                candidates = RETRIEVAL_METRIC_NAMES
-            case EvaluationCategory.AGENT:
-                candidates = AGENT_METRIC_NAMES
-            case EvaluationCategory.WORKFLOW | EvaluationCategory.SNIPPET:
-                candidates = WORKFLOW_METRIC_NAMES
-            case _:
-                return []
-        return [m for m in candidates if m in _DEEPEVAL_METRIC_MAP]
-
-    def evaluate_llm(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.LLM)
-
-    def evaluate_retrieval(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.RETRIEVAL)
-
-    def evaluate_agent(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.AGENT)
-
-    def evaluate_workflow(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.WORKFLOW)
-
-    def _evaluate(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        category: EvaluationCategory,
-    ) -> list[EvaluationItemResult]:
-        """Core evaluation logic using DeepEval."""
-        model_wrapper = DifyModelWrapper(model_provider, model_name, tenant_id)
-        requested_metrics = metric_names or self.get_supported_metrics(category)
-
-        try:
-            return self._evaluate_with_deepeval(items, requested_metrics, category)
-        except ImportError:
-            logger.warning("DeepEval not installed, falling back to simple evaluation")
-            return self._evaluate_simple(items, requested_metrics, model_wrapper)
-
-    def _evaluate_with_deepeval(
-        self,
-        items: list[EvaluationItemInput],
-        requested_metrics: list[str],
-        category: EvaluationCategory,
-    ) -> list[EvaluationItemResult]:
-        """Evaluate using DeepEval library.
-
-        Builds LLMTestCase differently per category:
-        - LLM/Workflow: input=prompt, actual_output=output, retrieval_context=context
-        - Retrieval: input=query, actual_output=output, expected_output, retrieval_context=context
-        - Agent: input=query, actual_output=output
-        """
-        metric_pairs = _build_deepeval_metrics(requested_metrics)
-        if not metric_pairs:
-            logger.warning("No valid DeepEval metrics found for: %s", requested_metrics)
-            return [EvaluationItemResult(index=item.index) for item in items]
-
-        results: list[EvaluationItemResult] = []
-        for item in items:
-            test_case = self._build_test_case(item, category)
-            metrics: list[EvaluationMetric] = []
-            for canonical_name, metric in metric_pairs:
-                try:
-                    metric.measure(test_case)
-                    if metric.score is not None:
-                        metrics.append(EvaluationMetric(name=canonical_name, value=float(metric.score)))
-                except Exception:
-                    logger.exception(
-                        "Failed to compute metric %s for item %d",
-                        canonical_name,
-                        item.index,
-                    )
-            results.append(EvaluationItemResult(index=item.index, metrics=metrics))
-        return results
-
-    @staticmethod
-    def _build_test_case(item: EvaluationItemInput, category: EvaluationCategory) -> Any:
-        """Build a deepeval LLMTestCase with the correct fields per category."""
-        from deepeval.test_case import LLMTestCase
-
-        user_input = _format_input(item.inputs, category)
-
-        match category:
-            case EvaluationCategory.LLM | EvaluationCategory.WORKFLOW:
-                # faithfulness needs: input, actual_output, retrieval_context
-                # answer_relevancy needs: input, actual_output
-                return LLMTestCase(
-                    input=user_input,
-                    actual_output=item.output,
-                    expected_output=item.expected_output or None,
-                    retrieval_context=item.context or None,
-                )
-            case EvaluationCategory.RETRIEVAL:
-                # contextual_precision/recall needs: input, actual_output, expected_output, retrieval_context
-                return LLMTestCase(
-                    input=user_input,
-                    actual_output=item.output or "",
-                    expected_output=item.expected_output or "",
-                    retrieval_context=item.context or [],
-                )
-            case _:
-                return LLMTestCase(
-                    input=user_input,
-                    actual_output=item.output,
-                )
-
-    def _evaluate_simple(
-        self,
-        items: list[EvaluationItemInput],
-        requested_metrics: list[str],
-        model_wrapper: DifyModelWrapper,
-    ) -> list[EvaluationItemResult]:
-        """Simple LLM-as-judge fallback when DeepEval is not available."""
-        results: list[EvaluationItemResult] = []
-        for item in items:
-            metrics: list[EvaluationMetric] = []
-            for m_name in requested_metrics:
-                try:
-                    score = self._judge_with_llm(model_wrapper, m_name, item)
-                    metrics.append(EvaluationMetric(name=m_name, value=score))
-                except Exception:
-                    logger.exception("Failed to compute metric %s for item %d", m_name, item.index)
-            results.append(EvaluationItemResult(index=item.index, metrics=metrics))
-        return results
-
-    def _judge_with_llm(
-        self,
-        model_wrapper: DifyModelWrapper,
-        metric_name: str,
-        item: EvaluationItemInput,
-    ) -> float:
-        """Use the LLM to judge a single metric for a single item."""
-        prompt = self._build_judge_prompt(metric_name, item)
-        response = model_wrapper.invoke(prompt)
-        return self._parse_score(response)
-
-    @staticmethod
-    def _build_judge_prompt(metric_name: str, item: EvaluationItemInput) -> str:
-        """Build a scoring prompt for the LLM judge."""
-        parts = [
-            f"Evaluate the following on the metric '{metric_name}' using a scale of 0.0 to 1.0.",
-            f"\nInput: {item.inputs}",
-            f"\nOutput: {item.output}",
-        ]
-        if item.expected_output:
-            parts.append(f"\nExpected Output: {item.expected_output}")
-        if item.context:
-            parts.append(f"\nContext: {'; '.join(item.context)}")
-        parts.append("\nRespond with ONLY a single floating point number between 0.0 and 1.0, nothing else.")
-        return "\n".join(parts)
-
-    @staticmethod
-    def _parse_score(response: str) -> float:
-        """Parse a float score from LLM response."""
-        import re
-
-        cleaned = response.strip()
-        try:
-            score = float(cleaned)
-            return max(0.0, min(1.0, score))
-        except ValueError:
-            match = re.search(r"(\d+\.?\d*)", cleaned)
-            if match:
-                score = float(match.group(1))
-                return max(0.0, min(1.0, score))
-            return 0.0
-
-
-def _format_input(inputs: dict[str, Any], category: EvaluationCategory) -> str:
-    """Extract the user-facing input string from the inputs dict."""
-    match category:
-        case EvaluationCategory.LLM | EvaluationCategory.WORKFLOW:
-            return str(inputs.get("prompt", ""))
-        case EvaluationCategory.RETRIEVAL:
-            return str(inputs.get("query", ""))
-        case _:
-            return str(next(iter(inputs.values()), "")) if inputs else ""
-
-
-def _build_deepeval_metrics(requested_metrics: list[str]) -> list[tuple[str, Any]]:
-    """Build DeepEval metric instances from canonical metric names.
-
-    Returns a list of (canonical_name, metric_instance) pairs so that callers
-    can record the canonical name rather than the framework-internal class name.
-    """
-    try:
-        from deepeval.metrics import (
-            AnswerRelevancyMetric,
-            ContextualPrecisionMetric,
-            ContextualRecallMetric,
-            ContextualRelevancyMetric,
-            FaithfulnessMetric,
-            TaskCompletionMetric,
-            ToolCorrectnessMetric,
-        )
-
-        # Maps canonical name → deepeval metric class
-        deepeval_class_map: dict[str, Any] = {
-            EvaluationMetricName.FAITHFULNESS: FaithfulnessMetric,
-            EvaluationMetricName.ANSWER_RELEVANCY: AnswerRelevancyMetric,
-            EvaluationMetricName.CONTEXT_PRECISION: ContextualPrecisionMetric,
-            EvaluationMetricName.CONTEXT_RECALL: ContextualRecallMetric,
-            EvaluationMetricName.CONTEXT_RELEVANCE: ContextualRelevancyMetric,
-            EvaluationMetricName.TOOL_CORRECTNESS: ToolCorrectnessMetric,
-            EvaluationMetricName.TASK_COMPLETION: TaskCompletionMetric,
-        }
-
-        pairs: list[tuple[str, Any]] = []
-        for name in requested_metrics:
-            metric_class = deepeval_class_map.get(name)
-            if metric_class:
-                pairs.append((name, metric_class(threshold=0.5)))
-            else:
-                logger.warning("Metric '%s' is not supported by DeepEval, skipping", name)
-        return pairs
-    except ImportError:
-        logger.warning("DeepEval metrics not available")
-        return []

api/core/evaluation/frameworks/ragas/ragas_evaluator.py

@@ -1,345 +0,0 @@
-import logging
-from importlib import import_module
-from typing import Any
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.config_entity import RagasConfig
-from core.evaluation.entities.evaluation_entity import (
-    AGENT_METRIC_NAMES,
-    LLM_METRIC_NAMES,
-    RETRIEVAL_METRIC_NAMES,
-    WORKFLOW_METRIC_NAMES,
-    EvaluationCategory,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    EvaluationMetric,
-    EvaluationMetricName,
-)
-from core.evaluation.frameworks.ragas.ragas_model_wrapper import DifyModelWrapper
-
-logger = logging.getLogger(__name__)
-
-# Maps canonical EvaluationMetricName to the corresponding ragas metric class.
-# Metrics not listed here are unsupported by ragas and will be skipped.
-_RAGAS_METRIC_MAP: dict[EvaluationMetricName, str] = {
-    EvaluationMetricName.FAITHFULNESS: "Faithfulness",
-    EvaluationMetricName.ANSWER_RELEVANCY: "AnswerRelevancy",
-    EvaluationMetricName.ANSWER_CORRECTNESS: "AnswerCorrectness",
-    EvaluationMetricName.SEMANTIC_SIMILARITY: "SemanticSimilarity",
-    EvaluationMetricName.CONTEXT_PRECISION: "ContextPrecision",
-    EvaluationMetricName.CONTEXT_RECALL: "ContextRecall",
-    EvaluationMetricName.CONTEXT_RELEVANCE: "ContextRelevance",
-    EvaluationMetricName.TOOL_CORRECTNESS: "ToolCallAccuracy",
-}
-
-
-class RagasEvaluator(BaseEvaluationInstance):
-    """RAGAS framework adapter for evaluation."""
-
-    def __init__(self, config: RagasConfig):
-        self.config = config
-
-    def get_supported_metrics(self, category: EvaluationCategory) -> list[str]:
-        match category:
-            case EvaluationCategory.LLM:
-                candidates = LLM_METRIC_NAMES
-            case EvaluationCategory.RETRIEVAL:
-                candidates = RETRIEVAL_METRIC_NAMES
-            case EvaluationCategory.AGENT:
-                candidates = AGENT_METRIC_NAMES
-            case EvaluationCategory.WORKFLOW | EvaluationCategory.SNIPPET:
-                candidates = WORKFLOW_METRIC_NAMES
-            case _:
-                return []
-        return [m for m in candidates if m in _RAGAS_METRIC_MAP]
-
-    def evaluate_llm(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.LLM)
-
-    def evaluate_retrieval(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.RETRIEVAL)
-
-    def evaluate_agent(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.AGENT)
-
-    def evaluate_workflow(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-    ) -> list[EvaluationItemResult]:
-        return self._evaluate(items, metric_names, model_provider, model_name, tenant_id, EvaluationCategory.WORKFLOW)
-
-    def _evaluate(
-        self,
-        items: list[EvaluationItemInput],
-        metric_names: list[str],
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        category: EvaluationCategory,
-    ) -> list[EvaluationItemResult]:
-        """Core evaluation logic using RAGAS."""
-        model_wrapper = DifyModelWrapper(model_provider, model_name, tenant_id)
-        requested_metrics = metric_names or self.get_supported_metrics(category)
-
-        try:
-            return self._evaluate_with_ragas(items, requested_metrics, model_wrapper, category)
-        except ImportError:
-            logger.warning("RAGAS not installed, falling back to simple evaluation")
-            return self._evaluate_simple(items, requested_metrics, model_wrapper)
-
-    def _evaluate_with_ragas(
-        self,
-        items: list[EvaluationItemInput],
-        requested_metrics: list[str],
-        model_wrapper: DifyModelWrapper,
-        category: EvaluationCategory,
-    ) -> list[EvaluationItemResult]:
-        """Evaluate using RAGAS library.
-
-        Builds SingleTurnSample differently per category to match ragas requirements:
-        - LLM/Workflow: user_input=prompt, response=output, reference=expected_output
-        - Retrieval: user_input=query, reference=expected_output, retrieved_contexts=context
-        - Agent: Not supported via EvaluationDataset (requires message-based API)
-        """
-        from ragas import evaluate as ragas_evaluate
-        from ragas.dataset_schema import EvaluationDataset
-
-        samples: list[Any] = []
-        for item in items:
-            sample = self._build_sample(item, category)
-            samples.append(sample)
-
-        dataset = EvaluationDataset(samples=samples)
-
-        ragas_metrics = self._build_ragas_metrics(requested_metrics)
-        if not ragas_metrics:
-            logger.warning("No valid RAGAS metrics found for: %s", requested_metrics)
-            return [EvaluationItemResult(index=item.index, actual_output=item.output) for item in items]
-
-        try:
-            result = ragas_evaluate(
-                dataset=dataset,
-                metrics=ragas_metrics,
-                llm=model_wrapper,
-            )
-
-            results: list[EvaluationItemResult] = []
-            result_df = result.to_pandas()
-            for i, item in enumerate(items):
-                metrics: list[EvaluationMetric] = []
-                for m_name in requested_metrics:
-                    if m_name in result_df.columns:
-                        score = result_df.iloc[i][m_name]
-                        if score is not None and not (isinstance(score, float) and score != score):
-                            metrics.append(EvaluationMetric(name=m_name, value=float(score)))
-                results.append(EvaluationItemResult(index=item.index, metrics=metrics, actual_output=item.output))
-            return results
-        except Exception:
-            logger.exception("RAGAS evaluation failed, falling back to simple evaluation")
-            return self._evaluate_simple(items, requested_metrics, model_wrapper)
-
-    @staticmethod
-    def _build_sample(item: EvaluationItemInput, category: EvaluationCategory) -> Any:
-        """Build a ragas SingleTurnSample with the correct fields per category.
-
-        ragas metric field requirements:
-        - faithfulness:       user_input, response, retrieved_contexts
-        - answer_relevancy:   user_input, response
-        - answer_correctness: user_input, response, reference
-        - semantic_similarity: user_input, response, reference
-        - context_precision:  user_input, reference, retrieved_contexts
-        - context_recall:     user_input, reference, retrieved_contexts
-        - context_relevance:  user_input, retrieved_contexts
-        """
-        from ragas.dataset_schema import SingleTurnSample
-
-        user_input = _format_input(item.inputs, category)
-
-        match category:
-            case EvaluationCategory.LLM:
-                # response = actual LLM output, reference = expected output
-                return SingleTurnSample(
-                    user_input=user_input,
-                    response=item.output,
-                    reference=item.expected_output or "",
-                    retrieved_contexts=item.context or [],
-                )
-            case EvaluationCategory.RETRIEVAL:
-                # context_precision/recall only need reference + retrieved_contexts
-                return SingleTurnSample(
-                    user_input=user_input,
-                    reference=item.expected_output or "",
-                    retrieved_contexts=item.context or [],
-                )
-            case _:
-                return SingleTurnSample(
-                    user_input=user_input,
-                    response=item.output,
-                )
-
-    def _evaluate_simple(
-        self,
-        items: list[EvaluationItemInput],
-        requested_metrics: list[str],
-        model_wrapper: DifyModelWrapper,
-    ) -> list[EvaluationItemResult]:
-        """Simple LLM-as-judge fallback when RAGAS is not available."""
-        results: list[EvaluationItemResult] = []
-        for item in items:
-            metrics: list[EvaluationMetric] = []
-            for m_name in requested_metrics:
-                try:
-                    score = self._judge_with_llm(model_wrapper, m_name, item)
-                    metrics.append(EvaluationMetric(name=m_name, value=score))
-                except Exception:
-                    logger.exception("Failed to compute metric %s for item %d", m_name, item.index)
-            results.append(EvaluationItemResult(index=item.index, metrics=metrics, actual_output=item.output))
-        return results
-
-    def _judge_with_llm(
-        self,
-        model_wrapper: DifyModelWrapper,
-        metric_name: str,
-        item: EvaluationItemInput,
-    ) -> float:
-        """Use the LLM to judge a single metric for a single item."""
-        prompt = self._build_judge_prompt(metric_name, item)
-        response = model_wrapper.invoke(prompt)
-        return self._parse_score(response)
-
-    @staticmethod
-    def _build_judge_prompt(metric_name: str, item: EvaluationItemInput) -> str:
-        """Build a scoring prompt for the LLM judge."""
-        parts = [
-            f"Evaluate the following on the metric '{metric_name}' using a scale of 0.0 to 1.0.",
-            f"\nInput: {item.inputs}",
-            f"\nOutput: {item.output}",
-        ]
-        if item.expected_output:
-            parts.append(f"\nExpected Output: {item.expected_output}")
-        if item.context:
-            parts.append(f"\nContext: {'; '.join(item.context)}")
-        parts.append("\nRespond with ONLY a single floating point number between 0.0 and 1.0, nothing else.")
-        return "\n".join(parts)
-
-    @staticmethod
-    def _parse_score(response: str) -> float:
-        """Parse a float score from LLM response."""
-        import re
-
-        cleaned = response.strip()
-        try:
-            score = float(cleaned)
-            return max(0.0, min(1.0, score))
-        except ValueError:
-            match = re.search(r"(\d+\.?\d*)", cleaned)
-            if match:
-                score = float(match.group(1))
-                return max(0.0, min(1.0, score))
-            return 0.0
-
-    @staticmethod
-    def _build_ragas_metrics(requested_metrics: list[str]) -> list[Any]:
-        """Build RAGAS metric instances from canonical metric names."""
-        try:
-            metrics_module = _import_ragas_metrics_module()
-
-            # Maps canonical name → ragas metric class
-            ragas_class_map: dict[str, Any] = {
-                EvaluationMetricName.FAITHFULNESS: getattr(metrics_module, "Faithfulness"),
-                EvaluationMetricName.ANSWER_RELEVANCY: getattr(metrics_module, "AnswerRelevancy"),
-                EvaluationMetricName.ANSWER_CORRECTNESS: getattr(metrics_module, "AnswerCorrectness"),
-                EvaluationMetricName.SEMANTIC_SIMILARITY: getattr(metrics_module, "SemanticSimilarity"),
-                EvaluationMetricName.CONTEXT_PRECISION: getattr(metrics_module, "ContextPrecision"),
-                EvaluationMetricName.CONTEXT_RECALL: getattr(metrics_module, "ContextRecall"),
-                EvaluationMetricName.CONTEXT_RELEVANCE: getattr(metrics_module, "ContextRelevance"),
-                EvaluationMetricName.TOOL_CORRECTNESS: getattr(metrics_module, "ToolCallAccuracy"),
-            }
-
-            metrics = []
-            for name in requested_metrics:
-                metric_class = ragas_class_map.get(name)
-                if metric_class:
-                    if name == EvaluationMetricName.ANSWER_CORRECTNESS:
-                        # ragas answer_correctness blends factuality with semantic
-                        # similarity. The latter requires an embeddings backend,
-                        # which is not wired through Dify's evaluation stack yet.
-                        # Keep the metric usable by relying on the factuality
-                        # component only for now.
-                        metrics.append(metric_class(weights=[1.0, 0.0], embeddings=_NoopRagasEmbeddings()))
-                    else:
-                        metrics.append(metric_class())
-                else:
-                    logger.warning("Metric '%s' is not supported by RAGAS, skipping", name)
-            return metrics
-        except ImportError:
-            logger.warning("RAGAS metrics not available")
-            return []
-
-
-def _import_ragas_metrics_module() -> Any:
-    """Load ragas metric classes across supported ragas versions.
-
-    ragas 0.3.x exposes metric classes from ``ragas.metrics`` while some older
-    versions used ``ragas.metrics.collections``. Support both so worker
-    environments do not silently drop all metrics because of a module path
-    mismatch.
-    """
-    try:
-        return import_module("ragas.metrics")
-    except ImportError:
-        return import_module("ragas.metrics.collections")
-
-
-class _NoopRagasEmbeddings:
-    """Placeholder embeddings for ragas metrics whose embedding branch is disabled.
-
-    ragas eagerly injects a default embeddings backend for any metric that
-    subclasses ``MetricWithEmbeddings``. For answer_correctness we currently
-    disable the semantic-similarity weight, so no real embedding call should
-    happen. Supplying this placeholder keeps ragas from constructing its
-    default OpenAI embeddings client during setup.
-    """
-
-    async def aembed_query(self, text: str) -> list[float]:
-        del text
-        return [0.0]
-
-    async def aembed_documents(self, texts: list[str]) -> list[list[float]]:
-        return [[0.0] for _ in texts]
-
-
-def _format_input(inputs: dict[str, Any], category: EvaluationCategory) -> str:
-    """Extract the user-facing input string from the inputs dict."""
-    match category:
-        case EvaluationCategory.LLM | EvaluationCategory.WORKFLOW:
-            return str(inputs.get("prompt", ""))
-        case EvaluationCategory.RETRIEVAL:
-            return str(inputs.get("query", ""))
-        case _:
-            return str(next(iter(inputs.values()), "")) if inputs else ""

api/core/evaluation/frameworks/ragas/ragas_model_wrapper.py

@@ -1,165 +0,0 @@
-import asyncio
-import logging
-from typing import Any
-
-from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
-from langchain_core.outputs import ChatGeneration, LLMResult
-from langchain_core.prompt_values import PromptValue
-
-try:
-    from ragas.llms.base import BaseRagasLLM
-except ImportError:
-    class BaseRagasLLM:  # type: ignore[no-redef]
-        """Lightweight shim so the module stays importable without ragas installed."""
-
-        def __init__(self, *args: Any, **kwargs: Any) -> None:
-            del args, kwargs
-
-        @staticmethod
-        def get_temperature(n: int) -> float:
-            return 0.3 if n > 1 else 1e-8
-
-logger = logging.getLogger(__name__)
-
-
-class DifyModelWrapper(BaseRagasLLM):
-    """Bridge Dify model invocation to ragas and fallback LLM-as-judge flows.
-
-    ragas can accept a custom ``BaseRagasLLM`` instance. Using one here keeps
-    evaluation requests on Dify's provider stack instead of falling back to
-    ragas' default OpenAI factory, which would require standalone environment
-    credentials and bypass tenant-scoped model configuration.
-    """
-
-    model_provider: str
-    model_name: str
-    tenant_id: str
-    user_id: str | None
-
-    def __init__(self, model_provider: str, model_name: str, tenant_id: str, user_id: str | None = None):
-        super().__init__()
-        self.model_provider = model_provider
-        self.model_name = model_name
-        self.tenant_id = tenant_id
-        self.user_id = user_id
-
-    def _get_model_instance(self) -> Any:
-        from core.plugin.impl.model_runtime_factory import create_plugin_model_manager
-        from graphon.model_runtime.entities.model_entities import ModelType
-
-        model_manager = create_plugin_model_manager(tenant_id=self.tenant_id, user_id=self.user_id)
-        model_instance = model_manager.get_model_instance(
-            tenant_id=self.tenant_id,
-            provider=self.model_provider,
-            model_type=ModelType.LLM,
-            model=self.model_name,
-        )
-        return model_instance
-
-    def invoke(self, prompt: str) -> str:
-        """Invoke the configured Dify model with a plain-text evaluation prompt."""
-        from graphon.model_runtime.entities.message_entities import SystemPromptMessage, UserPromptMessage
-
-        model_instance = self._get_model_instance()
-        result = model_instance.invoke_llm(
-            prompt_messages=[
-                SystemPromptMessage(content="You are an evaluation judge. Answer precisely and concisely."),
-                UserPromptMessage(content=prompt),
-            ],
-            model_parameters={"temperature": 0.0},
-            stream=False,
-        )
-        return result.message.content
-
-    def generate_text(
-        self,
-        prompt: PromptValue,
-        n: int = 1,
-        temperature: float = 1e-8,
-        stop: list[str] | None = None,
-        callbacks: Any = None,
-    ) -> LLMResult:
-        """Implement ragas' sync LLM interface on top of Dify's model runtime."""
-        del callbacks  # Dify's invocation path does not currently use LangChain callbacks here.
-        prompt_messages = _convert_prompt_value(prompt)
-        model_instance = self._get_model_instance()
-
-        generations: list[list[ChatGeneration]] = [[]]
-        completions = max(1, n)
-        for _ in range(completions):
-            result = model_instance.invoke_llm(
-                prompt_messages=prompt_messages,
-                model_parameters={"temperature": temperature},
-                stop=stop,
-                stream=False,
-            )
-            text = result.message.content
-            generations[0].append(
-                ChatGeneration(
-                    text=text,
-                    message=AIMessage(content=text, response_metadata={"finish_reason": "stop"}),
-                    generation_info={"finish_reason": "stop"},
-                )
-            )
-
-        return LLMResult(generations=generations)
-
-    async def agenerate_text(
-        self,
-        prompt: PromptValue,
-        n: int = 1,
-        temperature: float | None = None,
-        stop: list[str] | None = None,
-        callbacks: Any = None,
-    ) -> LLMResult:
-        """Async ragas hook backed by the sync Dify invocation path."""
-        return await asyncio.to_thread(
-            self.generate_text,
-            prompt,
-            n,
-            self.get_temperature(n) if temperature is None else temperature,
-            stop,
-            callbacks,
-        )
-
-
-def _convert_prompt_value(prompt: PromptValue) -> list[Any]:
-    """Translate LangChain prompt values into graphon prompt messages."""
-    from graphon.model_runtime.entities.message_entities import (
-        AssistantPromptMessage,
-        SystemPromptMessage,
-        UserPromptMessage,
-    )
-
-    prompt_messages: list[Any] = []
-    for message in prompt.to_messages():
-        content = _message_content_to_text(message)
-        if isinstance(message, SystemMessage):
-            prompt_messages.append(SystemPromptMessage(content=content))
-        elif isinstance(message, AIMessage):
-            prompt_messages.append(AssistantPromptMessage(content=content))
-        elif isinstance(message, HumanMessage):
-            prompt_messages.append(UserPromptMessage(content=content))
-        else:
-            prompt_messages.append(UserPromptMessage(content=content))
-
-    return prompt_messages
-
-
-def _message_content_to_text(message: BaseMessage) -> str:
-    """Flatten LangChain message content into a plain-text string for Dify."""
-    if isinstance(message.content, str):
-        return message.content
-
-    if isinstance(message.content, list):
-        parts: list[str] = []
-        for block in message.content:
-            if isinstance(block, str):
-                parts.append(block)
-            elif isinstance(block, dict):
-                text = block.get("text")
-                if text:
-                    parts.append(str(text))
-        return "\n".join(part for part in parts if part)
-
-    return str(message.content or "")

api/core/evaluation/judgment/processor.py

@@ -1,160 +0,0 @@
-"""Judgment condition processor for evaluation metrics.
-
-Evaluates pass/fail judgment conditions against evaluation metric values.
-Each condition uses ``variable_selector`` (``[node_id, metric_name]``) to
-look up the metric value, then delegates the actual comparison to the
-workflow condition engine (``graphon.utils.condition.processor``).
-
-The processor is intentionally decoupled from evaluation frameworks and
-runners.  It operates on plain ``dict`` mappings and can be invoked
-anywhere that already has per-item metric results.
-"""
-
-import logging
-from collections.abc import Sequence
-from typing import Any, cast
-
-from core.evaluation.entities.judgment_entity import (
-    JudgmentCondition,
-    JudgmentConditionResult,
-    JudgmentConfig,
-    JudgmentResult,
-)
-from graphon.utils.condition.entities import SupportedComparisonOperator
-from graphon.utils.condition.processor import _evaluate_condition  # pyright: ignore[reportPrivateUsage]
-
-logger = logging.getLogger(__name__)
-
-_UNARY_OPERATORS = frozenset({"null", "not null", "empty", "not empty"})
-
-
-class JudgmentProcessor:
-    @staticmethod
-    def evaluate(
-        metric_values: dict[tuple[str, str], Any],
-        config: JudgmentConfig,
-    ) -> JudgmentResult:
-        """Evaluate all judgment conditions against the given metric values.
-
-        Args:
-            metric_values: Mapping of ``(node_id, metric_name)`` → metric
-                value (e.g. ``{("node_abc", "faithfulness"): 0.85}``).
-            config: The judgment configuration with logical_operator and
-                conditions.
-
-        Returns:
-            JudgmentResult with overall pass/fail and per-condition details.
-        """
-        if not config.conditions:
-            return JudgmentResult(
-                passed=True,
-                logical_operator=config.logical_operator,
-                condition_results=[],
-            )
-
-        condition_results: list[JudgmentConditionResult] = []
-
-        for condition in config.conditions:
-            result = JudgmentProcessor._evaluate_single_condition(metric_values, condition)
-            condition_results.append(result)
-
-            if config.logical_operator == "and" and not result.passed:
-                return JudgmentResult(
-                    passed=False,
-                    logical_operator=config.logical_operator,
-                    condition_results=condition_results,
-                )
-            if config.logical_operator == "or" and result.passed:
-                return JudgmentResult(
-                    passed=True,
-                    logical_operator=config.logical_operator,
-                    condition_results=condition_results,
-                )
-
-        if config.logical_operator == "and":
-            final_passed = all(r.passed for r in condition_results)
-        else:
-            final_passed = any(r.passed for r in condition_results)
-
-        return JudgmentResult(
-            passed=final_passed,
-            logical_operator=config.logical_operator,
-            condition_results=condition_results,
-        )
-
-    @staticmethod
-    def _evaluate_single_condition(
-        metric_values: dict[tuple[str, str], Any],
-        condition: JudgmentCondition,
-    ) -> JudgmentConditionResult:
-        """Evaluate a single judgment condition.
-
-        Steps:
-          1. Extract ``(node_id, metric_name)`` from ``variable_selector``.
-          2. Look up the metric value from ``metric_values``.
-          3. Delegate comparison to the workflow condition engine.
-        """
-        selector = condition.variable_selector
-        if len(selector) < 2:
-            return JudgmentConditionResult(
-                variable_selector=selector,
-                comparison_operator=condition.comparison_operator,
-                expected_value=condition.value,
-                actual_value=None,
-                passed=False,
-                error=f"variable_selector must have at least 2 elements, got {len(selector)}",
-            )
-
-        node_id, metric_name = selector[0], selector[1]
-        actual_value = metric_values.get((node_id, metric_name))
-
-        if actual_value is None and condition.comparison_operator not in _UNARY_OPERATORS:
-            return JudgmentConditionResult(
-                variable_selector=selector,
-                comparison_operator=condition.comparison_operator,
-                expected_value=condition.value,
-                actual_value=None,
-                passed=False,
-                error=f"Metric '{metric_name}' on node '{node_id}' not found in evaluation results",
-            )
-
-        try:
-            expected = condition.value
-            # Numeric operators need the actual value coerced to int/float
-            # so that the workflow engine's numeric assertions work correctly.
-            coerced_actual: object = actual_value
-            if (
-                condition.comparison_operator in {"=", "≠", ">", "<", "≥", "≤"}
-                and actual_value is not None
-                and not isinstance(actual_value, (int, float, bool))
-            ):
-                coerced_actual = float(actual_value)
-
-            passed = _evaluate_condition(
-                operator=cast(SupportedComparisonOperator, condition.comparison_operator),
-                value=coerced_actual,
-                expected=cast(str | Sequence[str] | bool | Sequence[bool] | None, expected),
-            )
-
-            return JudgmentConditionResult(
-                variable_selector=selector,
-                comparison_operator=condition.comparison_operator,
-                expected_value=expected,
-                actual_value=actual_value,
-                passed=passed,
-            )
-        except Exception as e:
-            logger.warning(
-                "Judgment condition evaluation failed for [%s, %s]: %s",
-                node_id,
-                metric_name,
-                str(e),
-            )
-            return JudgmentConditionResult(
-                variable_selector=selector,
-                comparison_operator=condition.comparison_operator,
-                expected_value=condition.value,
-                actual_value=actual_value,
-                passed=False,
-                error=str(e),
-            )

api/core/evaluation/runners/__init__.py

@@ -1,52 +0,0 @@
-from sqlalchemy import select
-from sqlalchemy.orm import Session
-
-from models import Account, App, CustomizedSnippet, TenantAccountJoin
-
-
-def get_service_account_for_app(session: Session, app_id: str) -> Account:
-    """Get the creator account for an app with tenant context set up.
-
-    This follows the same pattern as BaseTraceInstance.get_service_account_with_tenant().
-    """
-    app = session.scalar(select(App).where(App.id == app_id))
-    if not app:
-        raise ValueError(f"App with id {app_id} not found")
-
-    if not app.created_by:
-        raise ValueError(f"App with id {app_id} has no creator")
-
-    account = session.scalar(select(Account).where(Account.id == app.created_by))
-    if not account:
-        raise ValueError(f"Creator account not found for app {app_id}")
-
-    current_tenant = session.query(TenantAccountJoin).filter_by(account_id=account.id, current=True).first()
-    if not current_tenant:
-        raise ValueError(f"Current tenant not found for account {account.id}")
-
-    account.set_tenant_id(current_tenant.tenant_id)
-    return account
-
-
-def get_service_account_for_snippet(session: Session, snippet_id: str) -> Account:
-    """Get the creator account for a snippet with tenant context set up.
-
-    Mirrors :func:`get_service_account_for_app` but queries CustomizedSnippet.
-    """
-    snippet = session.scalar(select(CustomizedSnippet).where(CustomizedSnippet.id == snippet_id))
-    if not snippet:
-        raise ValueError(f"Snippet with id {snippet_id} not found")
-
-    if not snippet.created_by:
-        raise ValueError(f"Snippet with id {snippet_id} has no creator")
-
-    account = session.scalar(select(Account).where(Account.id == snippet.created_by))
-    if not account:
-        raise ValueError(f"Creator account not found for snippet {snippet_id}")
-
-    current_tenant = session.query(TenantAccountJoin).filter_by(account_id=account.id, current=True).first()
-    if not current_tenant:
-        raise ValueError(f"Current tenant not found for account {account.id}")
-
-    account.set_tenant_id(current_tenant.tenant_id)
-    return account

api/core/evaluation/runners/agent_evaluation_runner.py

@@ -1,66 +0,0 @@
-import logging
-from collections.abc import Mapping
-from typing import Any
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.evaluation_entity import (
-    DefaultMetric,
-    EvaluationDatasetInput,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    NodeInfo,
-)
-from core.evaluation.runners.base_evaluation_runner import BaseEvaluationRunner
-from graphon.node_events import NodeRunResult
-
-logger = logging.getLogger(__name__)
-
-
-class AgentEvaluationRunner(BaseEvaluationRunner):
-    """Runner for agent evaluation: collects tool calls and final output."""
-
-    def __init__(self, evaluation_instance: BaseEvaluationInstance):
-        super().__init__(evaluation_instance)
-
-    def evaluate_metrics(
-        self,
-        node_run_result_list: list[NodeRunResult],
-        default_metric: DefaultMetric,
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        dataset_items: list[EvaluationDatasetInput] | None = None,
-        node_info: NodeInfo | None = None,
-    ) -> list[EvaluationItemResult]:
-        """Compute agent evaluation metrics."""
-        if not node_run_result_list:
-            return []
-        merged_items = self._merge_results_into_items(node_run_result_list)
-        return self.evaluation_instance.evaluate_agent(
-            merged_items, [default_metric.metric], model_provider, model_name, tenant_id
-        )
-
-    @staticmethod
-    def _merge_results_into_items(items: list[NodeRunResult]) -> list[EvaluationItemInput]:
-        """Create EvaluationItemInput list from NodeRunResult for agent evaluation."""
-        merged = []
-        for i, item in enumerate(items):
-            output = _extract_agent_output(item.outputs)
-            merged.append(
-                EvaluationItemInput(
-                    index=i,
-                    inputs=dict(item.inputs),
-                    output=output,
-                )
-            )
-        return merged
-
-
-def _extract_agent_output(outputs: Mapping[str, Any]) -> str:
-    """Extract the primary output text from agent NodeRunResult.outputs."""
-    if "answer" in outputs:
-        return str(outputs["answer"])
-    if "text" in outputs:
-        return str(outputs["text"])
-    values = list(outputs.values())
-    return str(values[0]) if values else ""

api/core/evaluation/runners/base_evaluation_runner.py

@@ -1,55 +0,0 @@
-"""Base evaluation runner.
-
-Provides the abstract interface for metric computation. Each concrete runner
-(LLM, Retrieval, Agent, Workflow, Snippet) implements ``evaluate_metrics``
-to compute scores for a specific node type.
-
-Orchestration (merging results from multiple runners, applying judgment, and
-persisting to the database) is handled by the evaluation task, not the runner.
-"""
-
-import logging
-from abc import ABC, abstractmethod
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.evaluation_entity import (
-    DefaultMetric,
-    EvaluationDatasetInput,
-    NodeInfo,
-    EvaluationItemResult,
-)
-from graphon.node_events import NodeRunResult
-
-logger = logging.getLogger(__name__)
-
-
-class BaseEvaluationRunner(ABC):
-    """Abstract base class for evaluation runners.
-
-    Runners are stateless metric calculators: they receive node execution
-    results and a metric specification, then return scored results.  They
-    do **not** touch the database or apply judgment logic.
-    """
-
-    def __init__(self, evaluation_instance: BaseEvaluationInstance):
-        self.evaluation_instance = evaluation_instance
-
-    @abstractmethod
-    def evaluate_metrics(
-        self,
-        node_run_result_list: list[NodeRunResult],
-        default_metric: DefaultMetric,
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        dataset_items: list[EvaluationDatasetInput] | None = None,
-        node_info: NodeInfo | None = None,
-    ) -> list[EvaluationItemResult]:
-        """Compute evaluation metrics on the collected results.
-
-        The returned ``EvaluationItemResult.index`` values are positional
-        (0-based) and correspond to the order of *node_run_result_list*.
-        The caller is responsible for mapping them back to the original
-        dataset indices.
-        """
-        ...

api/core/evaluation/runners/llm_evaluation_runner.py

@@ -1,107 +0,0 @@
-import logging
-import re
-from collections.abc import Mapping
-from typing import Any
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.evaluation_entity import (
-    DefaultMetric,
-    EvaluationDatasetInput,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    NodeInfo,
-)
-from core.evaluation.runners.base_evaluation_runner import BaseEvaluationRunner
-from graphon.node_events import NodeRunResult
-
-logger = logging.getLogger(__name__)
-
-
-class LLMEvaluationRunner(BaseEvaluationRunner):
-    """Runner for LLM evaluation: extracts prompts/outputs then evaluates."""
-
-    def __init__(self, evaluation_instance: BaseEvaluationInstance):
-        super().__init__(evaluation_instance)
-
-    def evaluate_metrics(
-        self,
-        node_run_result_list: list[NodeRunResult],
-        default_metric: DefaultMetric,
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        dataset_items: list[EvaluationDatasetInput] | None = None,
-        node_info: NodeInfo | None = None,
-    ) -> list[EvaluationItemResult]:
-        """Use the evaluation instance to compute LLM metrics."""
-        if not node_run_result_list:
-            return []
-        merged_items = self._merge_results_into_items(node_run_result_list, dataset_items, node_info)
-        return self.evaluation_instance.evaluate_llm(
-            merged_items, [default_metric.metric], model_provider, model_name, tenant_id
-        )
-
-    @staticmethod
-    def _merge_results_into_items(
-        items: list[NodeRunResult],
-        dataset_items: list[EvaluationDatasetInput] | None = None,
-        node_info: NodeInfo | None = None,
-    ) -> list[EvaluationItemInput]:
-        """Create new items from NodeRunResult for ragas evaluation.
-
-        Extracts prompts from process_data and concatenates them into a single
-        string with role prefixes (e.g. "system: ...\nuser: ...\nassistant: ...").
-        The last assistant message in outputs is used as the actual output.
-        """
-        merged = []
-        for i, item in enumerate(items):
-            prompts = item.process_data.get("prompts", [])
-            prompt = _format_prompts(prompts)
-            output = _extract_llm_output(item.outputs)
-            dataset_item = dataset_items[i] if dataset_items and i < len(dataset_items) else None
-            merged.append(
-                EvaluationItemInput(
-                    index=i,
-                    inputs={"prompt": prompt},
-                    output=output,
-                    expected_output=dataset_item.get_expected_output_for_node(node_info.title) if dataset_item else None,
-                    context=_extract_context_blocks(prompts),
-                )
-            )
-        return merged
-
-
-def _format_prompts(prompts: list[dict[str, Any]]) -> str:
-    """Concatenate a list of prompt messages into a single string for evaluation.
-
-    Each message is formatted as "role: text" and joined with newlines.
-    """
-    parts: list[str] = []
-    for msg in prompts:
-        role = msg.get("role", "unknown")
-        text = msg.get("text", "")
-        parts.append(f"{role}: {text}")
-    return "\n".join(parts)
-
-
-def _extract_llm_output(outputs: Mapping[str, Any]) -> str:
-    """Extract the LLM output text from NodeRunResult.outputs."""
-    if "text" in outputs:
-        return str(outputs["text"])
-    if "answer" in outputs:
-        return str(outputs["answer"])
-    values = list(outputs.values())
-    return str(values[0]) if values else ""
-
-
-def _extract_context_blocks(prompts: list[dict[str, Any]]) -> list[str] | None:
-    """Extract tagged context blocks from rendered prompts.
-
-    Evaluation only treats prompt content wrapped in ``<context>...</context>``
-    as retrieved evidence. This keeps faithfulness-style metrics opt-in and
-    avoids guessing which arbitrary prompt text should be considered context.
-    """
-    prompt_text = "\n".join(str(prompt.get("text", "")) for prompt in prompts)
-    matches = re.findall(r"<context>(.*?)</context>", prompt_text, flags=re.DOTALL)
-    contexts = [match.strip() for match in matches if match.strip()]
-    return contexts or None

api/core/evaluation/runners/retrieval_evaluation_runner.py

@@ -1,67 +0,0 @@
-import logging
-from typing import Any
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.evaluation_entity import (
-    DefaultMetric,
-    EvaluationDatasetInput,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    NodeInfo,
-)
-from core.evaluation.runners.base_evaluation_runner import BaseEvaluationRunner
-from graphon.node_events import NodeRunResult
-
-logger = logging.getLogger(__name__)
-
-
-class RetrievalEvaluationRunner(BaseEvaluationRunner):
-    """Runner for retrieval evaluation: performs knowledge base retrieval, then evaluates."""
-
-    def __init__(self, evaluation_instance: BaseEvaluationInstance):
-        super().__init__(evaluation_instance)
-
-    def evaluate_metrics(
-        self,
-        node_run_result_list: list[NodeRunResult],
-        default_metric: DefaultMetric,
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        dataset_items: list[EvaluationDatasetInput] | None = None,
-        node_info: NodeInfo | None = None,
-    ) -> list[EvaluationItemResult]:
-        """Compute retrieval evaluation metrics."""
-        if not node_run_result_list:
-            return []
-
-        merged_items = []
-        for i, node_result in enumerate(node_run_result_list):
-            outputs = node_result.outputs
-            query = self._extract_query(dict(node_result.inputs))
-            result_list = outputs.get("result", [])
-            contexts = [item.get("content", "") for item in result_list if item.get("content")]
-            output = "\n---\n".join(contexts)
-            dataset_item = dataset_items[i] if dataset_items and i < len(dataset_items) else None
-
-            merged_items.append(
-                EvaluationItemInput(
-                    index=i,
-                    inputs={"query": query},
-                    output=output,
-                    expected_output=dataset_item.get_expected_output_for_node(node_info.title) if dataset_item else None,
-                    context=contexts,
-                )
-            )
-
-        return self.evaluation_instance.evaluate_retrieval(
-            merged_items, [default_metric.metric], model_provider, model_name, tenant_id
-        )
-
-    @staticmethod
-    def _extract_query(inputs: dict[str, Any]) -> str:
-        for key in ("query", "question", "input", "text"):
-            if key in inputs:
-                return str(inputs[key])
-        values = list(inputs.values())
-        return str(values[0]) if values else ""

api/core/evaluation/runners/snippet_evaluation_runner.py

@@ -1,72 +0,0 @@
-"""Runner for Snippet evaluation.
-
-Snippets are essentially workflows, so we reuse ``evaluate_workflow`` from
-the evaluation instance for metric computation.
-"""
-
-import logging
-from collections.abc import Mapping
-from typing import Any
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.evaluation_entity import (
-    DefaultMetric,
-    EvaluationDatasetInput,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    NodeInfo,
-)
-from core.evaluation.runners.base_evaluation_runner import BaseEvaluationRunner
-from graphon.node_events import NodeRunResult
-
-logger = logging.getLogger(__name__)
-
-
-class SnippetEvaluationRunner(BaseEvaluationRunner):
-    """Runner for snippet evaluation: evaluates a published Snippet workflow."""
-
-    def __init__(self, evaluation_instance: BaseEvaluationInstance):
-        super().__init__(evaluation_instance)
-
-    def evaluate_metrics(
-        self,
-        node_run_result_list: list[NodeRunResult],
-        default_metric: DefaultMetric,
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        dataset_items: list[EvaluationDatasetInput] | None = None,
-        node_info: NodeInfo | None = None,
-    ) -> list[EvaluationItemResult]:
-        """Compute evaluation metrics for snippet outputs."""
-        if not node_run_result_list:
-            return []
-        merged_items = self._merge_results_into_items(node_run_result_list)
-        return self.evaluation_instance.evaluate_workflow(
-            merged_items, [default_metric.metric], model_provider, model_name, tenant_id
-        )
-
-    @staticmethod
-    def _merge_results_into_items(items: list[NodeRunResult]) -> list[EvaluationItemInput]:
-        """Create EvaluationItemInput list from NodeRunResult for snippet evaluation."""
-        merged = []
-        for i, item in enumerate(items):
-            output = _extract_snippet_output(item.outputs)
-            merged.append(
-                EvaluationItemInput(
-                    index=i,
-                    inputs=dict(item.inputs),
-                    output=output,
-                )
-            )
-        return merged
-
-
-def _extract_snippet_output(outputs: Mapping[str, Any]) -> str:
-    """Extract the primary output text from snippet NodeRunResult.outputs."""
-    if "answer" in outputs:
-        return str(outputs["answer"])
-    if "text" in outputs:
-        return str(outputs["text"])
-    values = list(outputs.values())
-    return str(values[0]) if values else ""

api/core/evaluation/runners/workflow_evaluation_runner.py

@@ -1,66 +0,0 @@
-import logging
-from collections.abc import Mapping
-from typing import Any
-
-from core.evaluation.base_evaluation_instance import BaseEvaluationInstance
-from core.evaluation.entities.evaluation_entity import (
-    DefaultMetric,
-    EvaluationDatasetInput,
-    EvaluationItemInput,
-    EvaluationItemResult,
-    NodeInfo,
-)
-from core.evaluation.runners.base_evaluation_runner import BaseEvaluationRunner
-from graphon.node_events import NodeRunResult
-
-logger = logging.getLogger(__name__)
-
-
-class WorkflowEvaluationRunner(BaseEvaluationRunner):
-    """Runner for workflow evaluation: executes workflow App in non-streaming mode."""
-
-    def __init__(self, evaluation_instance: BaseEvaluationInstance):
-        super().__init__(evaluation_instance)
-
-    def evaluate_metrics(
-        self,
-        node_run_result_list: list[NodeRunResult],
-        default_metric: DefaultMetric,
-        model_provider: str,
-        model_name: str,
-        tenant_id: str,
-        dataset_items: list[EvaluationDatasetInput] | None = None,
-        node_info: NodeInfo | None = None,
-    ) -> list[EvaluationItemResult]:
-        """Compute workflow evaluation metrics (end-to-end)."""
-        if not node_run_result_list:
-            return []
-        merged_items = self._merge_results_into_items(node_run_result_list)
-        return self.evaluation_instance.evaluate_workflow(
-            merged_items, [default_metric.metric], model_provider, model_name, tenant_id
-        )
-
-    @staticmethod
-    def _merge_results_into_items(items: list[NodeRunResult]) -> list[EvaluationItemInput]:
-        """Create EvaluationItemInput list from NodeRunResult for workflow evaluation."""
-        merged = []
-        for i, item in enumerate(items):
-            output = _extract_workflow_output(item.outputs)
-            merged.append(
-                EvaluationItemInput(
-                    index=i,
-                    inputs=dict(item.inputs),
-                    output=output,
-                )
-            )
-        return merged
-
-
-def _extract_workflow_output(outputs: Mapping[str, Any]) -> str:
-    """Extract the primary output text from workflow NodeRunResult.outputs."""
-    if "answer" in outputs:
-        return str(outputs["answer"])
-    if "text" in outputs:
-        return str(outputs["text"])
-    values = list(outputs.values())
-    return str(values[0]) if values else ""

api/core/helper/credential_utils.py

@@ -2,6 +2,7 @@
 Credential utility functions for checking credential existence and policy compliance.
 """
 
+from configs import dify_config
 from core.entities import PluginCredentialType
 
 
@@ -39,6 +40,16 @@ def is_credential_exists(credential_id: str, credential_type: "PluginCredentialT
         return False
 
 
+def runtime_check_credential_policy_compliance(
+    credential_id: str, provider: str, credential_type: "PluginCredentialType", check_existence: bool = True
+):
+    if dify_config.ENTERPRISE_DISABLE_RUNTIME_CREDENTIAL_CHECK:
+        return
+    check_credential_policy_compliance(
+        credential_id=credential_id, provider=provider, credential_type=credential_type, check_existence=check_existence
+    )
+
+
 def check_credential_policy_compliance(
     credential_id: str, provider: str, credential_type: "PluginCredentialType", check_existence: bool = True
 ) -> None:

api/core/llm_generator/llm_generator.py

@@ -13,8 +13,6 @@ from core.llm_generator.output_parser.rule_config_generator import RuleConfigGen
 from core.llm_generator.output_parser.suggested_questions_after_answer import SuggestedQuestionsAfterAnswerOutputParser
 from core.llm_generator.prompts import (
     CONVERSATION_TITLE_PROMPT,
-    DEFAULT_SUGGESTED_QUESTIONS_MAX_TOKENS,
-    DEFAULT_SUGGESTED_QUESTIONS_TEMPERATURE,
     GENERATOR_QA_PROMPT,
     JAVASCRIPT_CODE_GENERATOR_PROMPT_TEMPLATE,
     LLM_MODIFY_CODE_SYSTEM,
@@ -217,8 +215,8 @@ class LLMGenerator:
             else:
                 # Default-model generation keeps the built-in suggested-questions tuning.
                 model_parameters = {
-                    "max_tokens": DEFAULT_SUGGESTED_QUESTIONS_MAX_TOKENS,
-                    "temperature": DEFAULT_SUGGESTED_QUESTIONS_TEMPERATURE,
+                    "max_tokens": 2560,
+                    "temperature": 0.0,
                 }
                 stop = []
 
@@ -437,7 +435,7 @@ class LLMGenerator:
             stream=False,
         )
 
-        # Runtime type check since pyright has issues with the overload
+        # Runtime type check for overload narrowing.
         if not isinstance(result, LLMResult):
             raise TypeError("Expected LLMResult when stream=False")
         response = result

api/core/llm_generator/prompts.py

@@ -104,10 +104,6 @@ DEFAULT_SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
     '["question1","question2","question3"]\n'
 )
 
-DEFAULT_SUGGESTED_QUESTIONS_MAX_TOKENS = 256
-DEFAULT_SUGGESTED_QUESTIONS_TEMPERATURE = 0.0
-
-
 GENERATOR_QA_PROMPT = (
     "<Task> The user will send a long text. Generate a Question and Answer pairs only using the knowledge"
     " in the long text. Please think step by step."

api/core/mcp/types.py

@@ -2,7 +2,7 @@ from collections.abc import Callable
 from dataclasses import dataclass
 from typing import Annotated, Any, Literal
 
-from pydantic import BaseModel, ConfigDict, Field, FileUrl, RootModel
+from pydantic import BaseModel, ConfigDict, Field, FileUrl, RootModel, model_validator
 from pydantic.networks import AnyUrl, UrlConstraints
 
 """
@@ -173,7 +173,21 @@ class JSONRPCError(BaseModel):
 
 
 class JSONRPCMessage(RootModel[JSONRPCRequest | JSONRPCNotification | JSONRPCResponse | JSONRPCError]):
-    pass
+    @model_validator(mode="before")
+    @classmethod
+    def _select_message_type(
+        cls, value: Any
+    ) -> JSONRPCRequest | JSONRPCNotification | JSONRPCResponse | JSONRPCError | Any:
+        if isinstance(value, dict):
+            if "result" in value:
+                return JSONRPCResponse.model_validate(value)
+            if "error" in value:
+                return JSONRPCError.model_validate(value)
+            if "method" in value:
+                if "id" in value:
+                    return JSONRPCRequest.model_validate(value)
+                return JSONRPCNotification.model_validate(value)
+        return value
 
 
 class EmptyResult(Result):